Search results for: YouTube videos

Authors: Anton Stadler, Thorsten Ike

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In this paper, we present a video based smoke detection algorithm based on TVL1 optical flow estimation. The main part of the algorithm is an accumulating system for motion angles and upward motion speed of the flow field. We optimized the usage of TVL1 flow estimation for the detection of smoke with very low smoke density. Therefore, we use adapted flow parameters and estimate the flow field on difference images. We show in theory and in evaluation that this improves the performance of smoke detection significantly. We evaluate the smoke algorithm using videos with different smoke densities and different backgrounds. We show that smoke detection is very reliable in varying scenarios. Further we verify that our algorithm is very robust towards crowded scenes disturbance videos.

Keywords: low density, optical flow, upward smoke motion, video based smoke detection

Procedia PDF Downloads 329

Authors: Yu-Chu Yeh, WeiChin Hsu, Chih-Yen Chang

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Substitution, combination, modification, putting to other uses, elimination, and rearrangement (SCAMPER) has been regarded as an effective technique that provides a structured way to help people to produce creative ideas and solutions. Although some neuroscience studies regarding creativity training have been conducted, no study has focused on SCAMPER. This study therefore aimed at examining whether the learning of SCAMPER through video tutorials would result in alternations of neural activation. Thirty college students were randomly assigned to the experimental group or the control group. The experimental group was requested to watch SCAMPER videos, whereas the control group was asked to watch natural-scene videos which were regarded as neutral stimulating materials. Each participant was brain scanned in a Functional magnetic resonance imaging (fMRI) machine while undertaking a creativity test before and after watching the videos. Furthermore, a two-way ANOVA was used to analyze the interaction between groups (the experimental group; the control group) and tasks (C task; M task; X task). The results revealed that the left precuneus significantly activated in the interaction of groups and tasks, as well as in the main effect of group. Furthermore, compared with the control group, the experimental group had greater activation in the default mode network (left precuneus and left inferior parietal cortex) and the motor network (left postcentral gyrus and left supplementary area). The findings suggest that the SCAMPER training may facilitate creativity through the stimulation of the default mode network and the motor network.

Keywords: creativity, default mode network, neural activation, SCAMPER

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Authors: Pratik Dhabal Deo, Manoj P.

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With the increasing number of social media users, the amount of video content available has also significantly increased. Currently, the number of smartphone users is at its peak, and many are increasingly using their smartphones as their main photography and recording devices. There have been a lot of developments in the field of Video Quality Assessment (VQA) and metrics like VMAF, SSIM etc. are said to be some of the best performing metrics, but the evaluation of these metrics is dominantly done on professionally taken video contents using professional tools, lighting conditions etc. No study particularly pinpointing the performance of the metrics on the contents taken by users on very commonly available devices has been done. Datasets that contain a huge number of videos from different high-end devices make it difficult to analyze the performance of the metrics on the content from most used devices even if they contain contents taken in poor lighting conditions using lower-end devices. These devices face a lot of distortions due to various factors since the spectrum of contents recorded on these devices is huge. In this paper, we have presented an analysis of the objective VQA metrics on contents taken only from most used devices and their performance on them, focusing on full-reference metrics. To carry out this research, we created a custom dataset containing a total of 90 videos that have been taken from three most commonly used devices, and android smartphone, an IOS smartphone and a DSLR. On the videos taken on each of these devices, the six most common types of distortions that users face have been applied on addition to already existing H.264 compression based on four reference videos. These six applied distortions have three levels of degradation each. A total of the five most popular VQA metrics have been evaluated on this dataset and the highest values and the lowest values of each of the metrics on the distortions have been recorded. Finally, it is found that blur is the artifact on which most of the metrics didn’t perform well. Thus, in order to understand the results better the amount of blur in the data set has been calculated and an additional evaluation of the metrics was done using HEVC codec, which is the next version of H.264 compression, on the camera that proved to be the sharpest among the devices. The results have shown that as the resolution increases, the performance of the metrics tends to become more accurate and the best performing metric among them is VQM with very few inconsistencies and inaccurate results when the compression applied is H.264, but when the compression is applied is HEVC, SSIM and VMAF have performed significantly better.

Keywords: distortion, metrics, performance, resolution, video quality assessment

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Authors: Ayse Inel Manav, Nuray Simsek

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The number of people with dementia and the problems that are experienced by these people are increasing along with aging world population. This study was carried out to assess the effects of reminiscence therapy using internet videos on the cognitive condition and apathy levels of elderly people who had mild dementia and lived in nursing homes. This randomly controlled experimental study was conducted between 25 May-25 August 2016 in the nursing home, elderly care and rehabilitation centers in Adana and Seyhan, Turkey. A total of 32 individuals participated in this study, 16 in the experimental group and 16 in the control group. Data were collected using a personal information form developed on the basis of the published literature, the Standardized Mini Mental Test (SMMT) and the Apathy Rating Scale (ARS). The Clinical Research Ethics Committee's approval, written institutional permission, and the written consent of the participants were obtained before data collection. The individuals in the experimental group received reminiscence therapy using internet videos for 60 minutes one day a week for three months. During the same period, 25-30 minutes of unstructured interviews on subjects unrelated to reminiscence were carried out with individuals in the control group. The SMMT and ARS were administered before the applications in the experimental group and at the end of the third month. The collected data were analyzed using descriptive statistics (means, standard deviations, and frequencies) as well as Student's t-test, the Mann-Whitney U-test, and Wilcoxon's signed ranks test. In this study, the total SMMT post-test scores of the experimental group were higher than those of the control group (p = 0.001; p < 0.01). There was a difference between experimental and control groups' total SMMT post-test scores (p = 0.001; p < 0.01). The experimental group's ARS total post-test scores were higher than those of the control group (p = 0.001; p < 0.01). This study found that group reminiscence therapy using internet videos improved the cognitive functions and apathy levels of elderly individuals with mild dementia.

Keywords: apaty, cognitive testing, dementia, elderly, reminisence threapy

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Authors: W.Appamana, S. Jantasee, P. Siwarasak, T. Mueansichai, C. Kaewbuddee

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Heat transfer is important in chemical engineering field. We have to know how to predict rates of heat transfer in a variety of process situations. Therefore, heat transfer learning is one of the greatest challenges for undergraduate students in chemical engineering. To enhance student learning in classroom, active-learning method was proposed in a single classroom, using problems based on videos and creating video, think-pair-share and jigsaw technique. The result shows that active learning method can prevent copying of the solutions manual for students and improve average examination scores about 5% when comparing with students in traditional section. Overall, this project represents an effective type of class that motivates student-centric learning while enhancing self-motivation, creative thinking and critical analysis among students.

Keywords: active learning, student-created video, self-motivation, creative thinking

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Authors: Raquel Ramos López, Anissa El-Khattabi, Ana Lucila Sandoval Orozco, Luis Javier García Villalba

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An increasing number of mobile devices with integrated cameras has meant that most digital video comes from these devices. These digital videos can be made anytime, anywhere and for different purposes. They can also be shared on the Internet in a short period of time and may sometimes contain recordings of illegal acts. The need to reliably trace the origin becomes evident when these videos are used for forensic purposes. This work proposes an algorithm to identify the brand and model of mobile device which generated the video. Its procedure is as follows: after obtaining the relevant video information, a classification algorithm based on sensor noise and Wavelet Transform performs the aforementioned identification process. We also present experimental results that support the validity of the techniques used and show promising results.

Keywords: digital video, forensics analysis, key frame, mobile device, PRNU, sensor noise, source identification

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Authors: Alex Arghya Adhikari

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Gaming and esports industry is one of the biggest and fastest growing industries in the world. Globally people have started investing more in this industry since now people believe just like traditional sports, esports can also sustain their future. Last year in the month of December, the Indian government also recognised esports as an official sport but there has not been any positive initiative by the government in encouraging people to enter esports. This is a problem which cannot be overlooked since we are already in the digital age and gaming and esports is the future industry. There is a need for multiple effective marketing strategies by the game publishers to stabilize the esports in the country. Purpose: To observe the marketing-communication strategies that are implemented by Riot Games’ Valorant and how those strategies influence the consumer behavior and the esports of the game. Methodology: Activities over the internet related to the game like livestreams, discord chats, Instagram posts and YouTube videos over a period of two months have been collected through the Digital Ethnography. To support and validate the observations of the data collected, in-depth online interviews have been conducted which includes streamers, journalists, LAN experienced players and casual players. Findings: The game publisher through its Dynamic Competitive Gaming Experience and Community-Engaged Ecosystem succeeded in making the game a Recreational activity and a Community which goes beyond the In-game experiences which helped in understanding the impact of audience engagement on esports and the loopholes and setbacks of Indian esports. Conclusion: The study provides a comprehensive analysis of how Valorant's successful marketing and community engagement strategies have contributed to its global popularity and competitive esports environment. It highlights the various strategies employed by Riot Games to keep players engaged and connected, and also the challenges in the Indian esports landscape which differentiates it from the global competition.

Keywords: esports, valorant, marketing, consumer behaviour

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Authors: R. S. Remya, U. S. Sethulekshmi

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Detecting the authenticity of a video is an important issue in digital forensics as Video is used as a silent evidence in court such as in child pornography, movie piracy cases, insurance claims, cases involving scientific fraud, traffic monitoring etc. The biggest threat to video data is the availability of modern open video editing tools which enable easy editing of videos without leaving any trace of tampering. In this paper, we propose an efficient passive method for inter-frame video tampering detection, its type and location by estimating the optical flow of wavelet features of adjacent frames and thresholding the variation in the estimated feature. The performance of the algorithm is compared with the z-score thresholding and achieved an efficiency above 95% on all the tested databases. The proposed method works well for videos with dynamic (forensics) as well as static (surveillance) background.

Keywords: discrete wavelet transform, optical flow, optical flow variation, video tampering

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Authors: Harry J. Witchel, James Ackah, Carlos P. Santos, Nachiappan Chockalingam, Carina E. I. Westling

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Introduction: Proxemics is the study of how people perceive and use space. It is commonly proposed that when people like or engage with a person/object, they will move slightly closer to it, often quite subtly and subconsciously. Music videos are known to add entertainment value to a pop song. Our hypothesis was that by adding appropriately matched video to a pop song, it would lead to a net approach of the head to the monitor screen compared to simply listening to an audio-only version of the song. Methods: We presented to 27 participants (ages 21.00 ± 2.89, 15 female) seated in front of 47.5 x 27 cm monitor two musical stimuli in a counterbalanced order; all stimuli were based on music videos by the band OK Go: Here It Goes Again (HIGA, boredom ratings (0-100) = 15.00 ± 4.76, mean ± SEM, standard-error-of-the-mean) and Do What You Want (DWYW, boredom ratings = 23.93 ± 5.98), which did not differ in boredom elicited (P = 0.21, rank-sum test). Each participant experienced each song only once, and one song (counterbalanced) as audio-only versus the other song as a music video. The movement was measured by video-tracking using Kinovea 0.8, based on recording from a lateral aspect; before beginning, each participant had a reflective motion tracking marker placed on the outer canthus of the left eye. Analysis of the Kinovea X-Y coordinate output in comma-separated-variables format was performed in Matlab, as were non-parametric statistical tests. Results: We found that the audio-only stimuli (combined for both HIGA and DWYW, mean ± SEM, 35.71 ± 5.36) were significantly more boring than the music video versions (19.46 ± 3.83, P = 0.0066 Wilcoxon Signed Rank Test (WSRT), Cohen's d = 0.658, N = 28). We also found that participants' heads moved around twice as much during the audio-only versions (speed = 0.590 ± 0.095 mm/sec) compared to the video versions (0.301 ± 0.063 mm/sec, P = 0.00077, WSRT). However, the participants' mean head-to-screen distances were not detectably smaller (i.e. head closer to the screen) during the music videos (74.4 ± 1.8 cm) compared to the audio-only stimuli (73.9 ± 1.8 cm, P = 0.37, WSRT). If anything, during the audio-only condition, they were slightly closer. Interestingly, the ranges of the head-to-screen distances were smaller during the music video (8.6 ± 1.4 cm) compared to the audio-only (12.9 ± 1.7 cm, P = 0.0057, WSRT), the standard deviations were also smaller (P = 0.0027, WSRT), and their heads were held 7 mm higher (video 116.1 ± 0.8 vs. audio-only 116.8 ± 0.8 cm above floor, P = 0.049, WSRT). Discussion: As predicted, sitting and listening to experimenter-selected pop music was more boring than when the music was accompanied by a matched, professionally-made video. However, we did not find that the proxemics of the situation led to approaching the screen. Instead, adding video led to efforts to control the head to a more central and upright viewing position and to suppress head fidgeting.

Keywords: boredom, engagement, music videos, posture, proxemics

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Authors: Sharifa Alduraibi, Abir El Sadik, Ahmed Elzainy, Alaa Alduraibi, Ahmed Alsolai

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Introduction: Problem-based learning (PBL) is an active student-centered educational modality, influenced by the students' interest that required continuous motivation to improve their engagement. The new era of professional information technology facilitated the utilization of educational multimedia, such as videos, soundtracks, and photographs promoting students' learning. The aim of the present study was to introduce multimedia-enriched PBL scenarios for the first time in college of medicine, Qassim University, as an incentive for better students' engagement. In addition, students' performance and satisfaction were evaluated. Methodology: Two multimedia-enhanced PBL scenarios were implemented to the third years' students in the urinary system block. Radiological images, plain CT scan, and X-ray of the abdomen and renal nuclear scan correlated with their pathological gross photographs were added to the scenarios. One week before the first sessions, pre-recorded orientation videos for PBL tutors were submitted to clarify the multimedia incorporated in the scenarios. Other two traditional PBL scenarios devoid of multimedia demonstrating the pathological and radiological findings were designed. Results and Discussion: Comparison between the formative assessments' results by the end of the two PBL modalities was done. It revealed significant increase in students' engagement, critical thinking and practical reasoning skills during the multimedia-enhanced sessions. Students' perception survey showed great satisfaction with the new strategy. Conclusion: It could be concluded from the current work that multimedia created technology-based teaching strategy inspiring the student for self-directed thinking and promoting students' overall achievement.

Keywords: multimedia, pathology and radiology images, problem-based learning, videos

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Authors: Zeynep Turhan

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Digital tools can improve knowledge and awareness of strategies and skills for healthy and respectful intimate relationships. The website of the Healthy and Respectful Relationship Program has been developed and included five key videos about how to build healthy intimate relationships. This study examined the perspectives about informative videos by focusing on how individuals learn new information or challenge their preconceptions or attitudes regarding male privilege and women's oppression. Five individuals who received no-contact orders and attended group intervention were the sample of this study. The observation notes were the major methodology examining how participants responded to video tools. The data analysis method was the interpretative phenomenological analysis. The results showed that many participants found the tools useful in learning the types of violence and communication strategies. Nevertheless, obstacles to implementing some techniques were found in their relationships. These digital tools might enhance healthy and respectful relationships despite some limitations.

Keywords: healthy relationship, digital tools, intimate partner violence, perpetrators, video interventions

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Authors: Xuan (Iris) Li, Jenny Zhengye Hou, Greg Hearn

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Food waste is a global issue, with an estimated 30% to 50% of food created never being consumed. Therefore, it is vital to reduce food waste and convert wasted food into recyclable outputs. TikTok provides a simple way of creating and duetting videos in just a few steps by using templates with the same sound/vision/caption effects to produce personalized content – this is called a duet, which is revealing to study the impact of TikTok on wasting more food or saving food. The research focuses on examining food-related content on TikTok, with particular attention paid to two distinct themes, food waste pranks and food-saving practices, to understand the potential impacts of these themes on adolescents and their attitudes toward sustainable food consumption practices. Specifically, the analysis explores how TikTok content related to food waste and/or food saving may contribute to the normalization and promotion of either positive or negative food behaviours among young viewers. The research employed content analysis and semi-structured interviews to understand what factors contribute to the difference in popularity between food pranks and food-saving videos and insights from the former can be applied to the latter to increase their communication effectiveness. The first category of food content on TikTok under examination pertains to food waste, including videos featuring pranks and mukbang. These forms of content have the potential to normalize or even encourage food waste behaviours among adolescents, exacerbating the already significant food waste problem. The second category of TikTok food content under examination relates to food saving, for example, videos teaching viewers how to maximize the use of food to reduce waste. This type of content can potentially empower adolescents to act against food waste and foster positive and sustainable food practices in their communities. The initial findings of the study suggest that TikTok content related to pranks appears to be more popular among viewers than content focused on teaching people how to save food. Additionally, these types of videos are gaining fans at a faster rate than content promoting more sustainable food practices. However, we argue there is a great potential for social media platforms like TikTok to play an educative role in promoting positive behaviour change among young people by sharing engaging content suitable to target audiences. This research serves as the first to investigate the potential utility of TikTok in food waste reduction and underscores the important role social media platforms can play in promoting sustainable food practices. The findings will help governments, organizations, and communities promote tailored and effective interventions to reduce food waste and help achieve the United Nations’ sustainable development goal of halving food waste by 2030.

Keywords: food waste reduction, behaviour, social media, TikTok, adolescents

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Authors: M. Prema Kumar, P. Rajesh Kumar

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The increasing interest in image fusion (combining images of two or more modalities such as infrared and visible light radiation) has led to a need for accurate and reliable image assessment methods. This paper gives a novel approach of merging the information content from several videos taken from the same scene in order to rack up a combined video that contains the finest information coming from different source videos. This process is known as video fusion which helps in providing superior quality (The term quality, connote measurement on the particular application.) image than the source images. In this technique different sensors (whose redundant information can be reduced) are used for various cameras that are imperative for capturing the required images and also help in reducing. In this paper Image fusion technique based on multi-resolution singular value decomposition (MSVD) has been used. The image fusion by MSVD is almost similar to that of wavelets. The idea behind MSVD is to replace the FIR filters in wavelet transform with singular value decomposition (SVD). It is computationally very simple and is well suited for real time applications like in remote sensing and in astronomy.

Keywords: multi sensor image fusion, MSVD, image processing, monochrome video

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Authors: Qiang Zhang, Xiaojian Hu1

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Intersection is the place where vehicles and pedestrians must pass through, turn and evacuate. Obtaining the motion data of vehicles near the intersection is of great significance for transportation research. Since there are usually many targets and there are more conflicts between targets, this makes it difficult to obtain vehicle motion parameters in traffic videos of intersections. According to the characteristics of traffic videos, this paper applies video technology to realize the automated track, count and trajectory extraction of vehicles to collect traffic data by roadside surveillance cameras installed near the intersections. Based on the video recognition method, the vehicles in each lane near the intersection are tracked with extracting trajectory and counted respectively in various degrees of occlusion and visibility. The performances are compared with current recognized CPU-based algorithms of real-time tracking-by-detection. The speed of the presented system is higher than the others and the system has a better real-time performance. The accuracy of direction has reached about 94.99% on average, and the accuracy of classification and statistics has reached about 75.12% on average.

Keywords: tracking and statistics, vehicle, signalized intersection, motion parameter, trajectory

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Authors: I Putu Indra Kusuma

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The rapid development of Information and Communication Technology (ICT) tools has improved the implementation of flipped classrooms in English Language Teaching (ELT), especially in speaking course. Flipped classrooms have therefore evolved from the oldest version, which uses recorded videos to the newest one (3.0 version), which combines various materials and enables out-of-class interaction and learning engagement. However, how the latest version of flipped classrooms affects students’ speaking performance and influences students’ learning engagement remains unclear. This study therefore sought (1) to examine the effect of flipped classrooms 3.0 towards students’ speaking performance and (2) to explore the students’ learning engagement during the implementation of flipped classrooms in the speaking course. This study then employed explanatory sequential mixed-method design. This study conducted a quasi-experimental study by recruiting 164 twelfth grade students of a public senior high school in Indonesia as the sample. They were distributed into experimental (80 students) and control (84 students) groups. The experimental group was treated by implementing flipped classrooms with various use of ICT tools such as Schoology, Youtube, websites, and Flipgrid for eight weeks. Meanwhile, the control group implemented a conventional method. Furthermore, there were two variables examined in this study, such as the implementation of flipped classrooms 3.0 as the independent variable and students’ speaking performance as the dependent variable. The data of these two variables were then collected through administering a speaking test to both groups. The data from this experimental study were analyzed by using independent t-test analysis. Also, five students were invited to participate in semi-structured interviews to explore their learning engagement during the implementation of flipped classrooms. The findings revealed that there was a significant difference in students’ speaking performance between experimental where t (df = 162) = 5.810, p < 0.001, d = 0.91 in which experimental group performed better in speaking than the control group. Also, the results of interviews showed that the students had positive learning engagement during the implementation of flipped classrooms 3.0, especially on out-of-class interactions and face-to-face meetings. Some relevant implications to ELT, especially in speaking courses, are also drawn from the data findings. From the findings, it can be concluded that flipped classrooms 3.0 has a significant effect on students’ speaking performance and it promotes students’ learning engagement. Therefore, flipped classrooms 3.0 should be embraced as the newest version of flipped classrooms that promotes interaction outside the classrooms and learning engagement.

Keywords: Flipped Classrooms 3.0, learning engagement, teaching speaking with technology, technology-enhanced language learning

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Authors: Valentina Zhang

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While facial expression is a complex and individualized behavior, all facial emotion recognition (FER) systems known to us rely on a single facial representation and are trained on universal data. We conjecture that: (i) different facial representations can provide different, sometimes complementing views of emotions; (ii) when employed collectively in a discussion group setting, they enable more accurate emotion reading which is highly desirable in autism care and other applications context sensitive to errors. In this paper, we first study FER using pixel-based DL vs semantics-based DL in the context of deepfake videos. Our experiment indicates that while the semantics-trained model performs better with articulated facial feature changes, the pixel-trained model outperforms on subtle or rare facial expressions. Armed with these findings, we have constructed an adaptive FER system learning from both types of models for dyadic or small interacting groups and further leveraging the synthesized group emotions as the ground truth for individualized FER training. Using a collection of group conversation videos, we demonstrate that FER accuracy and personalization can benefit from such an approach.

Keywords: neurodivergence care, facial emotion recognition, deep learning, ground truth for supervised learning

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Authors: Insaf Bellamine, Hamid Tairi

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Detecting moving objects in sequences is an essential step for video analysis. This paper mainly contributes to the Color Space-Time Interest Points (CSTIP) extraction and detection. We propose a new method for detection of moving objects. Two main steps compose the proposed method. First, we suggest to apply the algorithm of the detection of Color Space-Time Interest Points (CSTIP) on both components of the Color Structure-Texture Image Decomposition which is based on a Partial Differential Equation (PDE): a color geometric structure component and a color texture component. A descriptor is associated to each of these points. In a second stage, we address the problem of grouping the points (CSTIP) into clusters. Experiments and comparison to other motion detection methods on challenging sequences show the performance of the proposed method and its utility for video analysis. Experimental results are obtained from very different types of videos, namely sport videos and animation movies.

Keywords: Color Space-Time Interest Points (CSTIP), Color Structure-Texture Image Decomposition, Motion Detection, clustering

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Authors: Naman Solanki, Souraj Mondal

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With the world moving towards online communication, the video datastore has exploded in the past few years. Consequently, it has become crucial to analyse participant’s engagement levels in online communication videos. Engagement prediction of people in videos can be useful in many domains, like education, client meetings, dating, etc. Video-level or frame-level prediction of engagement for a user involves the development of robust models that can capture facial micro-emotions efficiently. For the development of an engagement prediction model, it is necessary to have a widely-accepted standard dataset for engagement analysis. DAiSEE is one of the datasets which consist of in-the-wild data and has a gold standard annotation for engagement prediction. Earlier research done using the DAiSEE dataset involved training and testing standard models like CNN-based models, but the results were not satisfactory according to industry standards. In this paper, a multi-level classification approach has been introduced to create a more robust model for engagement analysis using the DAiSEE dataset. This approach has recorded testing accuracies of 0.638, 0.7728, 0.8195, and 0.866 for predicting boredom level, engagement level, confusion level, and frustration level, respectively.

Keywords: computer vision, engagement prediction, deep learning, multi-level classification

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Authors: Munaf Rashid

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For content-based human action retrieval systems, search accuracy is often inferior because of the following two reasons 1) global information pertaining to videos is totally ignored, only low level motion descriptors are considered as a significant feature to match the similarity between query and database videos, and 2) the semantic gap between the high level user concept and low level visual features. Hence, in this paper, we propose a method that will address these two issues and in doing so, this paper contributes in two ways. Firstly, we introduce a method that uses both global and local information in one framework for an action retrieval task. Secondly, to minimize the semantic gap, a user concept is involved by incorporating features weight updating (FWU) Relevance Feedback (RF) approach. We use statistical characteristics to dynamically update weights of the feature descriptors so that after every RF iteration feature space is modified accordingly. For testing and validation purpose two human action recognition datasets have been utilized, namely Weizmann and UCF. Results show that even with a number of visual challenges the proposed approach performs well.

Keywords: relevance feedback (RF), action retrieval, semantic gap, feature descriptor, codebook

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Authors: Van Thinh Bui, Anh Tuan Tran, Quoc Viet Ngo, The Bao Pham

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Video retrieval is a searching problem on videos or clips based on content in which they are relatively close to an input image or video. The application of this retrieval consists of selecting video in a folder or recognizing a human in security camera. However, some recent approaches have been in challenging problem due to the diversity of video types, frame transitions and camera positions. Besides, that an appropriate measures is selected for the problem is a question. In order to overcome all obstacles, we propose a content-based video retrieval system in some main steps resulting in a good performance. From a main video, we process extracting keyframes and principal objects using Segmentation of Aggregating Superpixels (SAS) algorithm. After that, Speeded Up Robust Features (SURF) are selected from those principal objects. Then, the model “Bag-of-words” in accompanied by SVM classification are applied to obtain the retrieval result. Our system is performed on over 300 videos in diversity from music, history, movie, sports, and natural scene to TV program show. The performance is evaluated in promising comparison to the other approaches.

Keywords: video retrieval, principal objects, keyframe, segmentation of aggregating superpixels, speeded up robust features, bag-of-words, SVM

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Authors: U. S. N. Raju, Kothuri Sai Kiran, Meena G. Kamal, Vinay Nikhil Pabba, Suresh Kanaparthi

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There is huge amount of lecture video data available for public use, and many more lecture videos are being created and uploaded every day. Searching for videos on required topics from this huge database is a challenging task. Therefore, an efficient method for video retrieval is needed. An approach for automated video indexing and video search in large lecture video archives is presented. As the amount of video lecture data is huge, it is very inefficient to do the processing in a centralized computation framework. Hence, Hadoop Framework for distributed computing for Big Video Data is used. First, step in the process is automatic video segmentation and key-frame detection to offer a visual guideline for the video content navigation. In the next step, we extract textual metadata by applying video Optical Character Recognition (OCR) technology on key-frames. The OCR and detected slide text line types are adopted for keyword extraction, by which both video- and segment-level keywords are extracted for content-based video browsing and search. The performance of the indexing process can be improved for a large database by using distributed computing on Hadoop framework.

Keywords: video lectures, big video data, video retrieval, hadoop

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Authors: Hector Barrios-Piña, Georgia García-Arellano, Salvador García-Rodríguez, Gerardo Bocanegra-García, Shashi Kant

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This work shows the methodology of application and the effectiveness of the Flipped Learning technique for Civil Engineering laboratory classes. It was experimented by some of the professors of the Department of Civil Engineering at Tecnológico de Monterrey while teaching their laboratory classes. A total of 28 videos were created. The videos primarily demonstrate instructions of the experimental practices other than the usage of tools and materials. The technique allowed the students to prepare for their classes in advance. A survey was conducted on the participating professors and students (semester of August-December 2019) to quantify the effectiveness of the Flipped Learning technique. The students reported it as an excellent way of improving their learning aptitude, including self-learning whereas, the professors felt it as an efficient technique for optimizing their class session, which also provided an extra slot for class-interaction. A comparison of grades was analyzed between the students of the traditional classes and with Flipped Learning. It did not distinguish the benefits of Flipped Learning. However, the positive responses from the students and the professors provide an impetus for continuing and promoting the Flipped Learning technique in future classes.

Keywords: flipped learning, laboratory classes, civil engineering, competences development

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Authors: Ganna Zakharova

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The persuasive influence of tourism promotional materials is very much experienced nowadays. In order to attract the attention of viewers, marketers choose various techniques in their digital texts. Video is an essential element for attraction and seduction; it is a trigger element for tourists. This solution for web marketing engages and convinces potential tourists to book a tourism product. Embedding video materials into a website provides useful information, create different feelings in viewers, and help them finalize their decisions. The present article discusses video solutions for health tourism websites used to allure potential tourists. The paper reviews the influential elements of persuasive tourism marketing videos. The article highlights how these components as persuasive strategies of tourism promotional materials can influence the decisions of tourism websites’ users. The result section provides the real examples of the deployment of the mentioned technique to convince the audience by the website of 'Karpaty' resort (Ukraine). This technique is worth attention as it plays an important role in the promotion of tourism services. The data collection of this study will provide updated information in relation to the rhetoric of tourism.

Keywords: tourism discourse, persuasive video, influential videos in marketing, persuasive discourse, tourism promotion

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Authors: Didarul Islam Manik

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The study was conducted to determine social media usage by the Millennial/young-adult generation in the U.S. and Bangladesh. It investigated what types of social media Millennials/young-adults use in their everyday lives; for what purpose they use social media; what are the significant differences between the two cultures in terms of social media use; and how the age of the respondents correlates with differences in social media use. Among the 409 respondents, 200 were selected from the University of South Dakota and 209 from the University of Dhaka, Bangladesh. The convenience sampling method was used to select the samples. A four-page questionnaire instrument was constructed with 19 closed-ended questions that collected 87 data points. The study considered the uses and gratifications and domestication of technology models as theoretical frameworks. The study found that the Millennials spend an average of 4.5 hours on the Internet daily. They spend an average of 134 minutes on social media every day. However, the U.S. Millennials spend more time (141 minutes) on social media than the Bangladeshis (127 minutes). The U.S. Millennials use various types of social media including Facebook, Twitter, YouTube, Instagram, Pinterest, SnapChat, Reddit, Imgur, etc. In contrast, Bangladeshis use Facebook, YouTube, and Google plus+. The Bangladeshis tended to spend more time on Facebook (107 minutes) than the Americans (57 minutes). The study found that the Millennials of the two countries use Facebook to fill their free time, acquire information, seek entertainment, and maintain existing relationships. However, Bangladeshis are more likely to use Facebook for the acquisition of information, entertainment, educational purposes, and connecting with the people closest to them. Millennials also use Twitter to fill their free time, acquire information, and for entertainment. The study found a statistically significant difference between female and male social media use. It also found a significant correlation between age and using Facebook for educational purposes; age and discussing and posting religious issues; and age and meeting with new people. There is also a correlation between age and the use of Twitter for spending time and seeking entertainment.

Keywords: American study, social media, millennial generation, South Asian studies

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Authors: Georgios Samaras

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New media such as Facebook, YouTube and Twitter introduced the world to a new era of instant communication. An era where online interactions could replace a lot of offline actions. Technology can create a mediated environment in which participants can communicate (one-to-one, one-to-many, and many-to-many) both synchronously and asynchronously and participate in reciprocal message exchanges. Currently, social networks are attracting similar academic attention to that of the internet after its mainstream implementation into public life. Websites and platforms are seen as the forefront of a new political change. There is a significant backdrop of previous methodologies employed to research the effects of social networks. New approaches are being developed to be able to adapt to the growth of social networks and the invention of new platforms. Golden Dawn was the first openly neo-Nazi party post World War II to win seats in the parliament of a European country. Its racist rhetoric and violent tactics on social networks were rewarded by their supporters, who in the face of Golden Dawn’s leaders saw a ‘new dawn’ in Greek politics. Mainstream media banned its leaders and members of the party indefinitely after Ilias Kasidiaris attacked Liana Kanelli, a member of the Greek Communist Party, on live television. This media ban was seen as a treasonous move by a significant percentage of voters, who believed that the system was desperately trying to censor Golden Dawn to favor mainstream parties. The shocking attack on live television received international coverage and while European countries were condemning this newly emerged neo-Nazi rhetoric, almost 7 percent of the Greek population rewarded Golden Dawn with 18 seats in the Greek parliament. Many seem to think that Golden Dawn mobilised its voters online and this approach played a significant role in spreading their message and appealing to wider audiences. No strict online censorship existed back in 2012 and although Golden Dawn was openly used neo-Nazi symbolism, it was allowed to use social networks without serious restrictions until 2017. This paper used qualitative methods to investigate Golden Dawn’s rise in social networks from 2012 to 2019. The focus of the content analysis was set on three social networking platforms: Facebook, Twitter and YouTube, while the existence of Golden Dawn’s website, which was used as a news sharing hub, was also taken into account. The content analysis included text and visual analyses that sampled content from their social networking pages to translate their political messaging through an ideological lens focused on extreme-right populism. The absence of hate speech regulations on social network platforms in 2012 allowed the free expression of those heavily ultranationalist and populist views, as they were employed by Golden Dawn in the Greek political scene. On YouTube, Facebook and Twitter, the influence of their rhetoric was particularly strong. Official channels and MPs profiles were investigated to explore the messaging in-depth and understand its ideological elements.

Keywords: populism, far-right, social media, Greece, golden dawn

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Authors: Ouafa Benaida, Abdelhamid Loukil, Adda Ali Pacha

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In recent years, the growing interest of scientists in the field of image processing and analysis of underwater images and videos has been strengthened following the emergence of new underwater exploration techniques, such as the emergence of autonomous underwater vehicles and the use of underwater image sensors facilitating the exploration of underwater mineral resources as well as the search for new species of aquatic life by biologists. Indeed, underwater images and videos have several defects and must be preprocessed before their analysis. Underwater landscapes are usually darkened due to the interaction of light with the marine environment: light is absorbed as it travels through deep waters depending on its wavelength. Additionally, light does not follow a linear direction but is scattered due to its interaction with microparticles in water, resulting in low contrast, low brightness, color distortion, and restricted visibility. The improvement of the underwater image is, therefore, more than necessary in order to facilitate its analysis. The research presented in this paper aims to implement and evaluate a set of classical techniques used in the field of improving the quality of underwater images in several color representation spaces. These methods have the particularity of being simple to implement and do not require prior knowledge of the physical model at the origin of the degradation.

Keywords: underwater image enhancement, histogram normalization, histogram equalization, contrast limited adaptive histogram equalization, single-scale retinex

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Authors: Mokhlisur Rahman

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Ocean inhibits one of the most complex ecosystems on the planet that regulates the earth's climate and weather by providing us with compatible weather to live. Ocean provides food by extending various ways of lifestyles that are dependent on it, transportation by accommodating the world's biggest carriers, recreation by offering its beauty in many moods, and home to countless species. At the essence of receiving various forms of entertainment, consumers choose to be close to the ocean while performing many fun activities. Which, at some point, upsets the stomach of the ocean by threatening marine life and the environment. Consumers throw the waste into the ocean after using it. Most of them are plastics that float over the ocean and turn into thousands of micro pieces that are hard to observe with the naked eye but easily eaten by the sea species. Eventually, that conflicts with the natural consumption process of any living species, making them sick. This information is not known by most consumers who go to the sea or seashores occasionally to spend time, nor is it widely discussed, which creates an information gap among consumers. However, advertising is a powerful tool to educate people about ocean pollution. This abstract analyzes three major ocean-saving advertisement campaigns that use innovative and advanced technology to get maximum exposure. The study collects data from the selected campaigns' websites and retrieves all available content related to messages, videos, and images. First, the SeaLegacy campaign uses stunning images to create awareness among the people; they use social media content, videos, and other educational content. They create content and strategies to build an emotional connection among the consumers that encourage them to move on an action. All the messages in their campaign empower consumers by using powerful words. Second, Ocean Conservancy Campaign uses social media marketing, events, and educational content to protect the ocean from various pollutants, including plastics, climate change, and overfishing. They use powerful images and videos of marine life. Their mission is to create evidence-based solutions toward a healthy ocean. Their message includes the message regarding the local communities along with the sea species. Third, ocean clean-up is a campaign that applies strategies using innovative technologies to remove plastic waste from the ocean. They use social media, digital, and email marketing to reach people and raise awareness. They also use images and videos to evoke an emotional response to take action. These tree advertisements use realistic images, powerful words, and the presence of living species in the imagery presentation, which are eye-catching and can grow emotional connection among the consumers. Identifying the effectiveness of the messages these advertisements carry and their strategies highlights the knowledge gap of mass people between real pollution and its consequences, making the message more accessible to the mass of people. This study aims to provide insights into the effectiveness of ocean-saving advertisement campaigns and their impact on the public's awareness of ocean conservation. The findings from this study help shape future campaigns.

Keywords: advertising-campaign, content-creation, images ocean-saving technology, videos

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Authors: Justin Tang

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Balance tests are frequently used to diagnose concussions on the sidelines of sporting events. Manual scoring, however, is labor intensive and subjective, and many concussions go undetected. This study institutes a novel approach to conducting the Balance Error Scoring System (BESS) more quantitatively using Microsoft’s gaming system Kinect, which uses a contactless sensor and several cameras to receive data and estimate body limb positions. Using a machine learning approach, Visual Gesture Builder, and a deterministic approach, MATLAB, we tested whether the Kinect can differentiate between “correct” and erroneous stances of the BESS. We created the two separate solutions by recording test videos to teach the Kinect correct stances and by developing a code using Java. Twenty-two subjects were asked to perform a series of BESS tests while the Kinect was collecting data. The Kinect recorded the subjects and mapped key joints onto their bodies to obtain angles and measurements that are interpreted by the software. Through VGB and MATLAB, the videos are analyzed to enumerate the number of errors committed during testing. The resulting statistics demonstrate a high correlation between manual scoring and the Kinect approaches, indicating the viability of the use of remote tracking devices in conducting concussion tests.

Keywords: automated, concussion detection, contactless sensors, microsoft kinect

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Authors: Sebastian Leal-Arenas

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TikTok’s influence on contemporary society is undeniable. The impact of the mobile app transcends entertainment, as shown by the growing presence of specialized accounts dedicated to providing educational content, particularly as it pertains to language learning. However, the prevailing trend on the platform is vocabulary and grammar acquisition, neglecting a critical component: pronunciation. This study examines English pronunciation materials available on TikTok by taking a comprehensive approach that incorporates established assessment tools, such as the Learning Object Review Instrument and the Framework for Language Learning App Evaluation. Furthermore, novel evaluation categories are introduced to provide a more holistic assessment of these educational resources. 60 English pronunciation videos were part of the analysis. The findings reveal that these audio-visual materials present clear audio bolstered by high-quality video content and automatically generated closed captions. These three components enhance the comprehensibility of the input, making these concise videos valuable assets for language learners. Nevertheless, certain deficiencies are observed, such as the lack of emphasis on specific segments and their relationship with articulators. Improvements and refinements are discussed, as well as their potential utility within the language classroom. This study contributes to the ongoing investigation of multimedia materials used for language teaching and emphasizes the need to adapt pronunciation instruction methods to today’s technology.

Keywords: pronunciation, segments, teaching materials, technology

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Authors: Esther Cabezas-Rivas

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Ordinary differential equations (ODE) are a fundamental part of the curriculum for most engineering degrees, and students typically have difficulties in the subsequent abstract mathematical calculations. To enhance their motivation and profit that they are digital natives, we propose a teamwork project that includes the creation of a video. It should explain how to model mathematically a real-world problem transforming it into an ODE, which should then be solved using the tools learned in the lectures. This idea was indeed implemented with first-year students of a BSc in Engineering and Management during the period of online learning caused by the outbreak of COVID-19 in Spain. Each group of 4 students was assigned a different topic: model a hot water heater, search for the shortest path, design the quickest route for delivery, cooling a computer chip, the shape of the hanging cables of the Golden Gate, detecting land mines, rocket trajectories, etc. These topics should be worked out through two complementary channels: a written report describing the problem and a 10-15 min video on the subject. The report includes the following items: description of the problem to be modeled, detailed obtention of the ODE that models the problem, its complete solution, and interpretation in the context of the original problem. We report the outcomes of this teaching in context and active learning experience, including the feedback received by the students. They highlighted the encouragement of creativity and originality, which are skills that they do not typically relate to mathematics. Additionally, the video format (unlike a common presentation) has the advantage of allowing them to critically review and self-assess the recording, repeating some parts until the result is satisfactory. As a side effect, they felt more confident about their oral abilities. In short, students agreed that they had fun preparing the video. They recognized that it was tricky to combine deep mathematical contents with entertainment since, without the latter, it is impossible to engage people to view the video till the end. Despite this difficulty, after the activity, they claimed to understand better the material, and they enjoyed showing the videos to family and friends during and after the project.

Keywords: active learning, contextual teaching, models in differential equations, student-produced videos

Procedia PDF Downloads 127