Search results for: vision picking

Authors: Hesheng Wang, Haoyu Wang, Chungang Zhuang

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Estimating the 6D pose of objects is a core step for robot bin-picking tasks. The problem is that various objects are usually randomly stacked with heavy occlusion in real applications. In this work, we propose a method to regress 6D poses by predicting three points for each object in the 3D point cloud through deep learning. To solve the ambiguity of symmetric pose, we propose a labeling method to help the network converge better. Based on the predicted pose, an iterative method is employed for pose optimization. In real-world experiments, our method outperforms the classical approach in both precision and recall.

Keywords: pose estimation, deep learning, point cloud, bin-picking, 3D computer vision

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Authors: Hsin-Yi Huang, Ming-Sheng Liu, Jiun-Yan Shiau

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Planning the order picking lists of warehouses to achieve when the costs associated with logistics on the operational performance is a significant challenge. In e-commerce era, this task is especially important productive processes are high. Nowadays, many order planning techniques employ supervised machine learning algorithms. However, the definition of which features should be processed by such algorithms is not a simple task, being crucial to the proposed technique’s success. Against this background, we consider whether unsupervised algorithms can enhance the planning of order-picking lists. A Zone2 picking approach, which is based on using clustering algorithms twice, is developed. A simplified example is given to demonstrate the merit of our approach.

Keywords: order picking, warehouse, clustering, unsupervised learning

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Authors: Safa Gharbi, Hayfa Zgaya, Nesrine Zoghlami, Slim Hammadi, Cyril De Barbarin, Laurent Vinatier, Christiane Coupier

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Increasing productivity and quality of service, improving the working comfort and ensuring the efficiency of all processes are important challenges for every warehouse. The order picking is recognized to be the most important and costly activity of all the process in warehouses. This paper presents a new approach using Augmented Reality (AR) in the field of logistics. It aims to create a Head-Up Display (HUD) interface with a Warehouse Management System (WMS), using AR glasses. Integrating AR technology allows the optimization of order picking by reducing time of picking process, increasing the efficiency and delivering quickly. The picker will be able to access immediately to all the information needed for his tasks. All the information is displayed when needed in the field of vision (FOV) of the operator, without any action requested from him. These research works are part of the industrial project RASL (Réalité Augmentée au Service de la Logistique) which gathers two major partners: the LAGIS (Laboratory of Automatics, Computer Engineering and Signal Processing in Lille-France) and Genrix Group, European leader in warehouses logistics, who provided his software for implementation, and his logistics expertise.

Keywords: Augmented Reality (AR), logistics and optimization, Warehouse Management System (WMS), Head-Up Display (HUD)

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Authors: Muhammad Umair, Tanveer Hussain, Khubab Shaker, Yasir Nawab, Muhammad Maqsood, Madeha Jabbar

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The term comfort is defined as 'the absence of unpleasantness or discomfort' or 'a neutral state compared to the more active state'. Comfort mainly is of three types: sensorial (tactile) comfort, psychological comfort and thermo-physiological comfort. Thermophysiological comfort is determined by the air permeability and moisture management properties of the garment. The aim of this study was to investigate the effect of weave structure and picking sequence on the comfort properties of woven fabrics. Six woven fabrics with two different weave structures i.e. 1/1 plain and 3/1 twill and three different picking sequences: (SPI, DPI, 3PI) were taken as input variables whereas air permeability, wetting time, wicking behavior and overall moisture management capability (OMMC) of fabrics were taken as response variables and a comparison is made of the effect of weave structure and picking sequence on the response variables. It was found that fabrics woven in twill weave design and with simultaneous triple pick insertion (3PI) give significantly better air permeability, shorter wetting time and better water spreading rate, as compared to plain woven fabrics and those with double pick insertion (DPI) or single pick insertion (SPI). It could be concluded that the thermophysiological comfort of woven fabrics may be significantly improved simply by selecting a suitable weave design and picking sequence.

Keywords: air permeability, picking sequence, thermophysiological comfort, weave design

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Authors: Thanakrit Taweesoontorn, Sarucha Yanyong, Poom Konghuayrob

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Robotic arms have gained popularity in various industries due to their accuracy and efficiency. This research proposes a method for bin-picking tasks using the Cobot, combining the YOLOv5 CNNs model for object detection and pose estimation with traditional feature detection (FAST), feature description (BRISK), and matching algorithms. By integrating these algorithms and utilizing a small-scale depth sensor camera for capturing depth and color images, the system achieves real-time object detection and accurate pose estimation, enabling the robotic arm to pick objects correctly in both position and orientation. Furthermore, the proposed method is implemented within the ROS framework to provide a seamless platform for robotic control and integration. This integration of robotics, cameras, and AI technology contributes to the development of industrial robotics, opening up new possibilities for automating challenging tasks and improving overall operational efficiency.

Keywords: robotic vision, image processing, applications of robotics, artificial intelligent

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Authors: Heiko Diefenbach, Christoph H. Glock

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Order picking, i.e., the order-based retrieval of items in a warehouse, is an important time- and cost-intensive process for many logistic systems. Despite the ongoing trend of automation, most order picking systems are still manual picker-to-parts systems, where human pickers walk through the warehouse to collect ordered items. Human work in warehouses is not free from errors, and order pickers may at times pick the wrong or the incorrect number of items. Errors can cause additional costs and significant correction efforts. Moreover, age might increase a person’s likelihood to make mistakes. Hence, the negative impact of picking errors might increase for an aging workforce currently witnessed in many regions globally. A significant amount of research has focused on making order picking systems more efficient. Among other factors, storage assignment, i.e., the assignment of items to storage locations (e.g., shelves) within the warehouse, has been subject to optimization. Usually, the objective is to assign items to storage locations such that order picking times are minimized. Surprisingly, there is a lack of research concerned with picking errors and respective prevention approaches. This paper hypothesize that the storage assignment of items can affect the probability of pick errors. For example, storing similar-looking items apart from one other might reduce confusion. Moreover, storing items that are hard to count or require a lot of counting at easy-to-access and easy-to-comprehend self heights might reduce the probability to pick the wrong number of items. Based on this hypothesis, the paper discusses how to incorporate error-prevention measures into mathematical models for storage assignment optimization. Various approaches with respective benefits and shortcomings are presented and mathematically modeled. To investigate the newly developed models further, they are compared to conventional storage assignment strategies in a computational study. The study specifically investigates how the importance of error prevention increases with pickers being more prone to errors due to age, for example. The results suggest that considering error-prevention measures for storage assignment can reduce error probabilities with only minor decreases in picking efficiency. The results might be especially relevant for an aging workforce.

Keywords: an aging workforce, error prevention, order picking, storage assignment

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Authors: Eugene Y. C. Wong

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The increased market competition, customer expectation, and warehouse operating cost in third-party logistics have motivated the continuous exploration in improving operation efficiency in warehouse logistics. Cargo tracing in ordering picking process consumes excessive time for warehouse operators when handling enormous quantities of goods flowing through the warehouse each day. Internet of Things (IoT) with mobile cargo tracing apps and database management systems are developed this research to facilitate and reduce the cargo tracing time in order picking process of a third-party logistics firm. An operation review is carried out in the firm with opportunities for improvement being identified, including inaccurate inventory record in warehouse management system, excessive tracing time on stored products, and product misdelivery. The facility layout has been improved by modifying the designated locations of various types of products. The relationship among the pick and pack processing time, cargo tracing time, delivery accuracy, inventory turnover, and inventory count operation time in the warehouse are evaluated. The correlation of the factors affecting the overall cycle time is analysed. A mobile app is developed with the use of MIT App Inventor and the Access management database to facilitate cargo tracking anytime anywhere. The information flow framework from warehouse database system to cloud computing document-sharing, and further to the mobile app device is developed. The improved performance on cargo tracing in the order processing cycle time of warehouse operators have been collected and evaluated. The developed mobile voice picking and tracking systems brings significant benefit to the third-party logistics firm, including eliminating unnecessary cargo tracing time in order picking process and reducing warehouse operators overtime cost. The mobile tracking device is further planned to enhance the picking time and cycle count of warehouse operators with voice picking system in the developed mobile apps as future development.

Keywords: warehouse, order picking process, cargo tracing, mobile app, third-party logistics

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Authors: Yuanqing Li, Changyi Lei, Zhaopeng Xue, Zhuo Zheng, Yanbo Long

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In agricultural production and breeding, implementing automatic picking robot in orchard farming to reduce human labour and error is challenging. The core function of it is automatic identification based on machine vision. This paper focuses on apple detection and counting in orchards and implements several deep learning methods. Extensive datasets are used and a semi-automatic annotation method is proposed. The proposed deep learning models are in state-of-the-art YOLO family. In view of the essence of the models with various backbones, a multi-dimensional comparison in details is made in terms of counting accuracy, mAP and model memory, laying the foundation for realising automatic precision agriculture.

Keywords: agricultural object detection, deep learning, machine vision, YOLO family

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Authors: Farzaneh Rajabighamchi, Stan van Hoesel, Christof Defryn

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The generalized traveling salesman problem (GTSP) is an extension of the traveling salesman problem (TSP) where the set of nodes is partitioned into clusters, and the salesman must visit exactly one node per cluster. In this research, we apply the definition of the GTSP to an order picker routing problem with multiple locations per product. As such, each product represents a cluster and its corresponding nodes are the locations at which the product can be retrieved. To pick a certain product item from the warehouse, the picker needs to visit one of these locations during its pick tour. As all products are scattered throughout the warehouse, the product clusters not separated geographically. We propose an exact LP model as well as heuristic and meta-heuristic solution algorithms for the order picking problem with multiple product locations.

Keywords: warehouse optimization, order picking problem, generalised travelling salesman problem, heuristic algorithm

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Authors: Sarah El-Gamal, Passent Hossam, Ahmed Abd El Aziz, Rojina Mahmoud, Ahmed Hassan, Dalia Hilal, Eman Ayman, Hana Haytham, Omar Khamis

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Several concerns fall upon the supply chain, especially the cold supply chain. According to the literature, the main challenges in the cold supply chain are the distribution and storage phases. In this research, researchers focused on the storage area, which contains several activities such as the picking activity that faces a lot of obstacles and challenges The implementation of IoT solutions enables businesses to monitor the temperature of food items, which is perhaps the most critical parameter in cold chains. Therefore, researchers proposed a practical solution that would help in eliminating the problems related to ineffective picking for products, especially fish and seafood products, by using IoT technology, most notably LiFi technology. Thus, guaranteeing sufficient picking, reducing waste, and consequently lowering costs. A prototype was specially designed and examined. This research is a single case study research. Two methods of data collection were used; observation and semi-structured interviews. Semi-structured interviews were conducted with managers and decision maker at Carrefour Alexandria to validate the problem and the proposed practical solution using IoTandLiFi technology. A total of three interviews were conducted. As a result, a SWOT analysis was achieved in order to highlight all the strengths and weaknesses of using the recommended Lifi solution in the picking process. According to the investigations, it was found that the use of IoT and LiFi technology is cost effective, efficient, and reduces human errors, minimize the percentage of product waste and thus save money and cost. Thus, increasing customer satisfaction and profits gained.

Keywords: cold supply chain, picking process, temperature control, IOT, warehousing, LIFI

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Authors: Anum Akhter, Sumaira Altaf

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Purpose: To study the effect of low vision devices i.e. telescope and magnifying glasses on distance visual acuity and near visual acuity of children with Stargardt’s disease. Setting: Low vision department, Alshifa Trust Eye Hospital, Rawalpindi, Pakistan. Methods: 52 children having Stargardt’s disease were included in the study. All children were diagnosed by pediatrics ophthalmologists. Comprehensive low vision assessment was done by me in Low vision clinic. Visual acuity was measured using ETDRS chart. Refraction and other supplementary tests were performed. Children with Stargardt’s disease were provided with different telescopes and magnifying glasses for improving far vision and near vision. Results: Out of 52 children, 17 children were males and 35 children were females. Distance visual acuity and near visual acuity improved significantly with low vision aid trial. All children showed visual acuity better than 6/19 with a telescope of higher magnification. Improvement in near visual acuity was also significant with magnifying glasses trial. Conclusions: Low vision aids are useful for improvement in visual acuity in children. Children with Stargardt’s disease who are having a problem in education and daily life activities can get help from low vision aids.

Keywords: Stargardt, s disease, low vision aids, telescope, magnifiers

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Authors: Stavros T. Ponis, George D. Plakas-Koumadorakis, Sotiris P. Gayialis

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Augmented Reality (AR) can be defined as a technology, which takes the capabilities of computer-generated display, sound, text and effects to enhance the user's real-world experience by overlaying virtual objects into the real world. By doing that, AR is capable of providing a vast array of work support tools, which can significantly increase employee productivity, enhance existing job training programs by making them more realistic and in some cases introduce completely new forms of work and task executions. One of the most promising AR industrial applications, as literature shows, is the use of Head Worn, monocular or binocular Displays (HWD) to support logistics and production operations, such as order picking, part assembly and maintenance. This paper presents the initial results of an ongoing research project for the introduction of a dedicated AR-HWD solution to the picking process of a Distribution Center (DC) in Greece operated by a large Telecommunication Service Provider (TSP). In that context, the proposed research aims to determine whether gamification elements should be integrated in the functional requirements of the AR solution, such as providing points for reaching objectives and creating leaderboards and awards (e.g. badges) for general achievements. Up to now, there is a an ambiguity on the impact of gamification in logistics operations since gamification literature mostly focuses on non-industrial organizational contexts such as education and customer/citizen facing applications, such as tourism and health. To the contrary, the gamification efforts described in this study focus in one of the most labor- intensive and workflow dependent logistics processes, i.e. Customer Order Picking (COP). Although introducing AR in COP, undoubtedly, creates significant opportunities for workload reduction and increased process performance the added value of gamification is far from certain. This paper aims to provide insights on the suitability and usefulness of AR-enhanced gamification in the hard and very demanding environment of a logistics center. In doing so, it will utilize a review of the current state-of-the art regarding gamification of production and logistics processes coupled with the results of questionnaire guided interviews with industry experts, i.e. logisticians, warehouse workers (pickers) and AR software developers. The findings of the proposed research aim to contribute towards a better understanding of AR-enhanced gamification, the organizational change it entails and the consequences it potentially has for all implicated entities in the often highly standardized and structured work required in the logistics setting. The interpretation of these findings will support the decision of logisticians regarding the introduction of gamification in their logistics processes by providing them useful insights and guidelines originating from a real life case study of a large DC operating more than 300 retail outlets in Greece.

Keywords: augmented reality, technology acceptance, warehouse management, vision picking, new forms of work, gamification

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Authors: Noga Bregman

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Accurate and efficient earthquake detection and phase picking are crucial for seismic hazard assessment and emergency response. This study introduces EQMamba, a deep-learning method that combines the strengths of the Earthquake Transformer and the Mamba model for simultaneous earthquake detection and phase picking. EQMamba leverages the computational efficiency of Mamba layers to process longer seismic sequences while maintaining a manageable model size. The proposed architecture integrates convolutional neural networks (CNNs), bidirectional long short-term memory (BiLSTM) networks, and Mamba blocks. The model employs an encoder composed of convolutional layers and max pooling operations, followed by residual CNN blocks for feature extraction. Mamba blocks are applied to the outputs of BiLSTM blocks, efficiently capturing long-range dependencies in seismic data. Separate decoders are used for earthquake detection, P-wave picking, and S-wave picking. We trained and evaluated EQMamba using a subset of the STEAD dataset, a comprehensive collection of labeled seismic waveforms. The model was trained using a weighted combination of binary cross-entropy loss functions for each task, with the Adam optimizer and a scheduled learning rate. Data augmentation techniques were employed to enhance the model's robustness. Performance comparisons were conducted between EQMamba and the EQTransformer over 20 epochs on this modest-sized STEAD subset. Results demonstrate that EQMamba achieves superior performance, with higher F1 scores and faster convergence compared to EQTransformer. EQMamba reached F1 scores of 0.8 by epoch 5 and maintained higher scores throughout training. The model also exhibited more stable validation performance, indicating good generalization capabilities. While both models showed lower accuracy in phase-picking tasks compared to detection, EQMamba's overall performance suggests significant potential for improving seismic data analysis. The rapid convergence and superior F1 scores of EQMamba, even on a modest-sized dataset, indicate promising scalability for larger datasets. This study contributes to the field of earthquake engineering by presenting a computationally efficient and accurate method for simultaneous earthquake detection and phase picking. Future work will focus on incorporating Mamba layers into the P and S pickers and further optimizing the architecture for seismic data specifics. The EQMamba method holds the potential for enhancing real-time earthquake monitoring systems and improving our understanding of seismic events.

Keywords: earthquake, detection, phase picking, s waves, p waves, transformer, deep learning, seismic waves

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Authors: Joseph C. Chen

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Machine vision system provides automatic inspection to reduce manufacturing costs considerably. However, only a few principles have been found to optimize machine vision system and help it function more accurately in industrial practice. Mostly, there were complicated and impractical design techniques to improve the accuracy of machine vision system. This paper discusses implementing the Six Sigma Define, Measure, Analyze, Improve, and Control (DMAIC) approach to optimize the setup parameters of machine vision system when it is used as a direct measurement technique. This research follows a case study showing how Six Sigma DMAIC methodology has been put into use.

Keywords: DMAIC, machine vision system, process capability, Taguchi Parameter Design

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Authors: G. N. Simonian, R. F. Basalah, F. T. Abd El Halim, F. F. Abd El Latif, A. M. Adel, A. M. El Shafey.

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Carboxymethyl cellulose (CMC) is an anionic water soluble polymer that has been introduced in paper coating as a strength agent. One of the main objectives of this research is to investigate the influence of CMC concentration in improving the strength properties of paper fiber. In this work, we coated the paper sheets; Xerox paper sheets by different concentration of carboxymethyl cellulose solution (0.1, 0.5, 1, 1.5, 2, 3%) w/v. The mechanical properties; breaking length and tearing resistance (tear factor) were measured for the treated and untreated paper specimens. The retained polymer in the coated paper samples were also calculated. The more the concentration of the coating material; CMC increases, the more the mechanical properties; breaking length and tear factor increases. It can be concluded that CMC enhance the improvement of the mechanical properties of paper sheets result in increasing paper stability. The aim of the present research was also to study the effects on the vessel element structure and vessel picking tendency of the coated paper sheets. In addition to the improved strength properties of the treated sheet, a significant decrease in the vessel picking tendency was expected whereas refining of the original paper sheets (untreated paper sheets) improved mainly the bonding ability of fibers, CMC effectively enhanced the bonding of vessels as well. Moreover, film structures were formed in the fibrillated areas of the coated paper specimens, and they were concluded to reinforce the bonding within the sheet. Also, fragmentation of vessel elements through CMC modification was found to be important and results in a decreasing picking tendency which reflects in a good printability. Moreover, Scanning – Electron Microscope (SEM) images are represented to specifically explain the improved bonding ability of vessels and fibers after CMC modification. Finally, CMC modification enhance paper mechanical properties and print quality.

Keywords: carboxymethyl cellulose (CMC), breaking length, tear factor, vessel picking, printing, concentration

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Authors: Henok Girma Abebe

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The Vision Zero is a long-term goal of preventing all road traffic fatalities and serious injuries which was first adopted in Sweden in 1997. It is based on the assumption that death and serious injury in the road system is morally unacceptable. In order to approach this end, vision zero has put in place strategies that are radically different from the traditional safety work. The vision zero, for instance, promoted the adoption of the best available technology to promote safety, and placed the ultimate responsibility for traffic safety on system designers. Despite Vision Zero’s moral appeal and its expansion to different safety areas and also parts of the world, important philosophical concerns related to the adoption and implementation of the vision zero remain to be addressed. Moreover, the vision zero goal has been criticized on different grounds. The aim of this paper is to identify and systematically categorize criticisms that have been put forward against vision zero. The findings of the paper are solely based on a critical analysis of secondary sources and snowball method is employed to identify the relevant philosophical and empirical literatures. Two general categories of criticisms on the vision zero goal are identified. The first category consists of criticisms that target the setting of vision zero as a ‘goal’ and some of the basic assumptions upon which the goal is based. Among others, the goal of achieving zero fatalities and serious injuries, together with vision zero’s lexicographical prioritization of safety has been criticized as unrealistic. The second category consists of criticisms that target the strategies put in place to achieve the goal of zero fatalities and serious injuries. For instance, Vision zero’s responsibility ascription for road safety and its rejection of cost-benefit analysis in the formulation and adoption of safety measures has both been criticized as counterproductive. In this category also falls the criticism that Vision Zero safety measures tend to be too paternalistic. Significant improvements have been recorded in road safety work since the adoption of vision zero, however, for the vision zero to even succeed more, it is important that issues and criticisms of philosophical nature associated with it are identified and critically dealt with.

Keywords: criticisms, systems approach, traffic safety, vision zero

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Authors: Ali Mohagheghzadeh, Samad Vaez Badiegard, Bita Shomali

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Nowadays, with the increase in population, the need for protein sources is increasing. Different bacteria can cause food poisoning while most of the symptoms of food poisoning are similar to those of gastrointestinal infections. As a result, the diagnosis of bacteria and viruses causing food poisoning would not be possible without a stool culture. Cases of food poisoning are often accompanied by gastrointestinal disorders such as diarrhea, vomit, and gastrointestinal stomach cramps. Thus, providing enough food, taking into account health issues has always been a concern of authorities. Since E. coli bacterium is one of the important indicators of food hygiene and quality, producing food without being contaminated by this bacterium is desired in the food industry. This study aimed at assessing the E. coli contamination of poultry meat produced in slaughterhouses. Samples were taken from critical areas of slaughterhouses, namely the feather picking area, viscera and carcass evacuation area the area after cooling chillers. The results showed that 60% of contamination occurs in feather picking area. Among antiseptic and detergent materials, the highest reduction belongs to Epimax.

Keywords: slaughterhouse, E. coli, Epimax, contamination

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Authors: Abdelkrim Belhaoua, Jean-Pierre Radoux

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In France, the railway network is one of the main transport infrastructures and is the second largest European network. Therefore, railway inspection is an important task in railway maintenance to ensure safety for passengers using significant means in personal and technical facilities. Artificial vision has recently been applied to several railway applications due to its potential to improve the efficiency and accuracy when analyzing large databases of acquired images. In this paper, we present a vision system able to detect fastening elements based on artificial vision approach. This system acquires railway images using a CCD camera installed under a control carriage. These images are stitched together before having processed. Experimental results are presented to show that the proposed method is robust for detection fasteners in a complex environment.

Keywords: computer vision, image processing, railway inspection, image stitching, fastener recognition, neural network

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Authors: Ava Dodd, Jonathan Adams

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The purpose of this study is to explore the characteristics of developing a machine learning application using synthetic data. The study is structured to develop the application for the purpose of deploying the computer vision model. The findings discuss the realities of attempting to develop a computer vision model for practical purpose, and detail the processes, tools, and techniques that were used to meet accuracy requirements. The research reveals that synthetic data represents another variable that can be adjusted to improve the performance of a computer vision model. Further, a suite of tools and tuning recommendations are provided.

Keywords: computer vision, machine learning, synthetic data, YOLOv4

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Authors: Aurelija Burinskiene

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This paper presents the study for an e-commerce warehouse. The study is aiming to improve order fulfillment activity by identifying the strategy presenting the best performance. A simulation model was proposed to reach the target of this research. This model enables various scenario tests in an e-commerce warehouse, allowing them to find out for the best order fulfillment strategy. By using simulation, model authors investigated customers’ orders representing on-line purchases for one month. Experiments were designed to evaluate various order picking methods applicable to the fulfillment of customers’ orders. The research uses cost components analysis and helps to identify the best possible order picking method improving the overall performance of e-commerce warehouse and fulfillment service to the customers. The results presented show that the application of order batching strategy is the most applicable because it brings distance savings of around 6.7 percentage. This result could be improved by taking an assortment clustering action until 8.34 percentage. So, the recommendations were given to apply the method for future e-commerce warehouse operations.

Keywords: e-commerce, order, fulfilment, strategy, simulation

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Authors: C. Vázquez, L. M. Gigirey, C. P. del Oro, S. Seoane

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Early detection of visual problems plays a key role in the aging process. However, although vision problems are common among older people, the percentage of aging people who perform regular optometric exams is low. In fact, uncorrected refractive errors are one of the main causes of visual impairment in this group of the population. Purpose: To evaluate functional vision of older residents in order to show the urgent need of visual screening programs in Galician nursing homes. Methodology: We examined 364 older adults aged 65 years and over. To measure vision of the daily living, we tested distance and near presenting visual acuity (binocular visual acuity with habitual correction if warn, directional E-Snellen) Presenting near vision was tested at the usual working distance. We defined visual impairment (distance and near) as a presenting visual acuity less than 0.3. Exclusion criteria included immobilized residents unable to reach the USC Dual Sensory Loss Unit for visual screening. Association between categorical variables was performed using chi-square tests. We used Pearson and Spearman correlation tests and the variance analysis to determine differences between groups of interest. Results: 23,1% of participants have visual impairment for distance vision and 16,4% for near vision. The percentage of residents with far and near visual impairment reaches 8,2%. As expected, prevalence of visual impairment increases with age. No differences exist with regard to the level of functional vision between gender. Differences exist between age group respect to distance vision, but not in case of near vision. Conclusion: prevalence of visual impairment is high among the older people tested in this pilot study. This means a high percentage of older people with limitations in their daily life activities. It is necessary to develop an effective vision screening program for early detection of vision problems in Galician nursing homes.

Keywords: functional vision, elders, aging, nursing homes

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Authors: Rafael Iliasov, Alessandro Golkar

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Object detection based on event vision has been a dynamically growing field in computer vision for the last 16 years. In this work, we create multiple channels from a single event camera and propose an event fusion method (EFM) to enhance object detection in event-based vision systems. Each channel uses a different accumulation buffer to collect events from the event camera. We implement YOLOv7 for object detection, followed by a fusion algorithm. Our multichannel approach outperforms single-channel-based object detection by 0.7% in mean Average Precision (mAP) for detection overlapping ground truth with IOU = 0.5.

Keywords: event camera, object detection with multimodal inputs, multichannel fusion, computer vision

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Authors: Ranitha Guna Selvi D, Ramakrishnan R, Mohideen Abdul Kader

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Purpose: To study the role of Vision centers in managing preventable blindness through refractive error correction in Rural South India. Methods: A retrospective analysis of patients attending 15 Vision centers in Rural South India from a period of January 2021 to December 2021 was done. Medical records of 10,85,81 patients both new and reviewed, 79,562 newly registered patients and 29,019 review patient’s from15 Vision centers were included for data analysis. All the patients registered at the vision center underwent basic eye examination, including visual acuity, IOP measurement, Slit-lamp examination, retinoscopy, Fundus examination etc. Results: A total of 1,08,581 patients were included in the study. Of the total 1,08,581 patients, 79,562 were newly registered patients at Vision center and 29,019 were review patients. Males were 52,201(48.1%) and Females were 56,308(51.9) among them. The mean age of all examined patients was 41.03 ± 20.9 years (Standard deviation) and ranged from 01 – 113 years. Presenting mean visual acuity was 0.31 ± 0.5 in the right eye and 0.31 ± 0.4 in the left eye. Of the 1,08,581 patients 22,770 patients had refractive error in right eye and 22,721 patients had uncorrected refractive error in left eye. Glass prescription was given to 17,178 (15.8%) patients. 8,109 (7.5%) patients were referred to the base hospital for specialty clinic expert opinion or for cataract surgery. Conclusion: Vision center utilizing teleconsultation for comprehensive eye screening unit is a very effective tool in reducing the avoidable visual impairment caused due to uncorrected refractive error. Vision Centre model is believed to be efficient as it facilitates early detection and management of uncorrected refractive errors.

Keywords: refractive error, uncorrected refractive error, vision center, vision technician, teleconsultation

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Authors: Najm Alotaibi

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Human motion capture has become one of the major area of interest in the field of computer vision. Some of the major application areas that have been rapidly evolving include the advanced human interfaces, virtual reality and security/surveillance systems. This study provides a brief overview of the techniques and applications used for the markerless human motion capture, which deals with analyzing the human motion in the form of mathematical formulations. The major contribution of this research is that it classifies the computer vision based techniques of human motion capture based on the taxonomy, and then breaks its down into four systematically different categories of tracking, initialization, pose estimation and recognition. The detailed descriptions and the relationships descriptions are given for the techniques of tracking and pose estimation. The subcategories of each process are further described. Various hypotheses have been used by the researchers in this domain are surveyed and the evolution of these techniques have been explained. It has been concluded in the survey that most researchers have focused on using the mathematical body models for the markerless motion capture.

Keywords: human motion capture, computer vision, vision-based, tracking

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Authors: Rodrigo C. Belleza, Jr., Roselyn A. Maaño, Karl Patrick E. Camota, Darwin Kim Q. Bulawan

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Eyes are an essential and conspicuous organ of the human body. Human eyes are outward and inward portals of the body that allows to see the outside world and provides glimpses into ones inner thoughts and feelings. Inevitable blindness and visual impairments may result from eye-related disease, trauma, or congenital or degenerative conditions that cannot be corrected by conventional means. The study emphasizes innovative tools that will serve as an aid to the blind and visually impaired (VI) individuals. The researchers fabricated a prototype that utilizes the Microsoft Kinect for Windows and Arduino microcontroller board. The prototype facilitates advanced gesture recognition, voice recognition, obstacle detection and indoor environment navigation. Open Computer Vision (OpenCV) performs image analysis, and gesture tracking to transform Kinect data to the desired output. A computer vision technology device provides greater accessibility for those with vision impairments.

Keywords: algorithms, blind, computer vision, embedded systems, image analysis

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Authors: Dzmitry M. Kabanau, Vladimir V. Kabanov, Yahor V. Lebiadok, Denis V. Shabrov, Pavel V. Shpak, Gevork T. Mikaelyan, Alexandr P. Bunichev

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This article is deal with the experimental investigations of the laser diode matrixes (LDM) based on the AlGaAs/GaAs heterostructures (lasing wavelength 790-880 nm) to find optimal LDM parameters for active vision systems. In particular, the dependence of LDM radiation pulse power on the pulse duration and LDA active layer heating as well as the LDM radiation divergence are discussed.

Keywords: active vision systems, laser diode matrixes, thermal properties, radiation divergence

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Authors: Siwei Chang, Heng Li, Haitao Wu, Xin Fang

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Construction robots are receiving more and more attention as a promising solution to the manpower shortage issue in the construction industry. The development of intelligent control techniques that assist in controlling the robots to avoid transparency and reflected building obstacles is crucial for guaranteeing the adaptability and flexibility of mobile construction robots in complex construction environments. With the boom of computer vision techniques, a number of studies have proposed vision-based methods for transparent obstacle avoidance to improve operation accuracy. However, vision-based methods are also associated with disadvantages such as high computational costs. To provide better perception and value evaluation, this study aims to analyze the performance of vision-based techniques for avoiding transparent building obstacles. To achieve this, commonly used sensors, including a lidar, an ultrasonic sensor, and a USB camera, are equipped on the robotic platform to detect obstacles. A Raspberry Pi 3 computer board is employed to compute data collecting and control algorithms. The turtlebot3 burger is employed to test the programs. On-site experiments are carried out to observe the performance in terms of success rate and detection distance. Control variables include obstacle shapes and environmental conditions. The findings contribute to demonstrating how effectively vision-based obstacle avoidance strategies for transparent building obstacle avoidance and provide insights and informed knowledge when introducing computer vision techniques in the aforementioned domain.

Keywords: construction robot, obstacle avoidance, computer vision, transparent obstacle

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Authors: Tatsuya Iizuka, Takushi Kawamorita, Tomoya Handa, Hitoshi Ishikawa

Abstract:

We report normative cone contrast sensitivity values and sensitivity and specificity values for a computer-based color vision test, the cone contrast test-HD (CCT-HD). The participants included 50 phakic eyes with normal color vision (NCV) and 20 dichromatic eyes (ten with protanopia and ten with deuteranopia). The CCT-HD was used to measure L, M, and S-CCT-HD scores (color vision deficiency, L-, M-cone logCS≦1.65, S-cone logCS≦0.425) to investigate the sensitivity and specificity of CCT-HD based on anomalous-type diagnosis with animalscope. The mean ± standard error L-, M-, S-cone logCS for protanopia were 0.90±0.04, 1.65±0.03, and 0.63±0.02, respectively; for deuteranopia 1.74±0.03, 1.31±0.03, and 0.61±0.06, respectively; and for age-matched NCV were 1.89±0.04, 1.84±0.04, and 0.60±0.03, respectively, with significant differences for each group except for S-CCT-HD (Bonferroni corrected α = 0.0167, p < 0.0167). The sensitivity and specificity of CCT-HD were 100% for protan and deutan in diagnosing abnormal types from 20 to 64 years of age, but the specificity decreased to 65% for protan and 55% for deutan in older persons > 65. CCT-HD is comparable to the diagnostic performance of the anomalous type in the anomaloscope for the 20-64-year-old age group. However, the results should be interpreted cautiously in those ≥ 65 years. They are more susceptible to acquired color vision deficiencies due to the yellowing of the crystalline lens and other factors.

Keywords: cone contrast test HD, color vision test, congenital color vision deficiency, red-green dichromacy, cone contrast sensitivity

Procedia PDF Downloads 101

Authors: Thibaut Lauwerier

Abstract:

This presentation will cover the vision of international organizations on the link between development and education. This issue is very relevant to address the general topic of the conference. 'Educating for development' is indeed at the heart of their discourse. For most of international organizations involved in education, it is important to invest in this field since it is at the service of development. The idea of this presentation is to better understand the vision of development according to these international organizations and how education can contribute to this type of development. To address this issue, we conducted a comparative study of three major international organizations (OECD, UNESCO and World Bank) influencing education policy at the international level. The data come from the strategic reports of these organizations over the period 1990-2015. The results show that the visions of development refer mainly to the neoliberal agenda, despite evolutions, even contradictions. And so, education must increase productivity, improve economic growth, etc. UNESCO, which has a less narrow conception of the development and therefore the aims of education, does not have the same means as the two other organizations to advocate for an alternative vision.

Keywords: development, education, international organizations, poilcy

Procedia PDF Downloads 221

Authors: Zahow Muoftah

Abstract:

Traditional manual visual grading of fruits has been one of the agricultural industry’s major challenges due to its laborious nature as well as inconsistency in the inspection and classification process. The main requirements for computer vision and visual processing are some effective techniques for identifying defects and estimating defect areas. Automated defect detection using computer vision and machine learning has emerged as a promising area of research with a high and direct impact on the visual inspection domain. Grading, sorting, and disease detection are important factors in determining the quality of fruits after harvest. Many studies have used computer vision to evaluate the quality level of fruits during post-harvest. Many studies have used computer vision to evaluate the quality level of fruits during post-harvest. Many studies have been conducted to identify diseases and pests that affect the fruits of agricultural crops. However, most previous studies concentrated solely on the diagnosis of a lesion or disease. This study focused on a comprehensive study to identify pests and diseases of apple and banana fruits using detection and classification defects on Banana and Apples by Computer Vision. As a result, the current article includes research from these domains as well. Finally, various pattern recognition techniques for detecting apple and banana defects are discussed.

Keywords: computer vision, banana, apple, detection, classification

Procedia PDF Downloads 106