Search results for: Speckle tracking
498 Segmentation of Breast Lesions in Ultrasound Images Using Spatial Fuzzy Clustering and Structure Tensors
Authors: Yan Xu, Toshihiro Nishimura
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Segmentation in ultrasound images is challenging due to the interference from speckle noise and fuzziness of boundaries. In this paper, a segmentation scheme using fuzzy c-means (FCM) clustering incorporating both intensity and texture information of images is proposed to extract breast lesions in ultrasound images. Firstly, the nonlinear structure tensor, which can facilitate to refine the edges detected by intensity, is used to extract speckle texture. And then, a spatial FCM clustering is applied on the image feature space for segmentation. In the experiments with simulated and clinical ultrasound images, the spatial FCM clustering with both intensity and texture information gets more accurate results than the conventional FCM or spatial FCM without texture information.
Keywords: fuzzy c-means, spatial information, structure tensor, ultrasound image segmentation
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1790497 Real-time Target Tracking Using a Pan and Tilt Platform
Authors: Moulay A. Akhloufi
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In recent years, we see an increase of interest for efficient tracking systems in surveillance applications. Many of the proposed techniques are designed for static cameras environments. When the camera is moving, tracking moving objects become more difficult and many techniques fail to detect and track the desired targets. The problem becomes more complex when we want to track a specific object in real-time using a moving Pan and Tilt camera system to keep the target within the image. This type of tracking is of high importance in surveillance applications. When a target is detected at a certain zone, the possibility of automatically tracking it continuously and keeping it within the image until action is taken is very important for security personnel working in very sensitive sites. This work presents a real-time tracking system permitting the detection and continuous tracking of targets using a Pan and Tilt camera platform. A novel and efficient approach for dealing with occlusions is presented. Also a new intelligent forget factor is introduced in order to take into account target shape variations and avoid learning non desired objects. Tests conducted in outdoor operational scenarios show the efficiency and robustness of the proposed approach.
Keywords: Tracking, surveillance, target detection, Pan and tilt.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1777496 Wavelet-Based Despeckling of Synthetic Aperture Radar Images Using Adaptive and Mean Filters
Authors: Syed Musharaf Ali, Muhammad Younus Javed, Naveed Sarfraz Khattak
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In this paper we introduced new wavelet based algorithm for speckle reduction of synthetic aperture radar images, which uses combination of undecimated wavelet transformation, wiener filter (which is an adaptive filter) and mean filter. Further more instead of using existing thresholding techniques such as sure shrinkage, Bayesian shrinkage, universal thresholding, normal thresholding, visu thresholding, soft and hard thresholding, we use brute force thresholding, which iteratively run the whole algorithm for each possible candidate value of threshold and saves each result in array and finally selects the value for threshold that gives best possible results. That is why it is slow as compared to existing thresholding techniques but gives best results under the given algorithm for speckle reduction.
Keywords: Brute force thresholding, directional smoothing, direction dependent mask, undecimated wavelet transformation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2868495 Vision Based People Tracking System
Authors: Boukerch Haroun, Luo Qing Sheng, Li Hua Shi, Boukraa Sebti
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In this paper we present the design and the implementation of a target tracking system where the target is set to be a moving person in a video sequence. The system can be applied easily as a vision system for mobile robot. The system is composed of two major parts the first is the detection of the person in the video frame using the SVM learning machine based on the “HOG” descriptors. The second part is the tracking of a moving person it’s done by using a combination of the Kalman filter and a modified version of the Camshift tracking algorithm by adding the target motion feature to the color feature, the experimental results had shown that the new algorithm had overcame the traditional Camshift algorithm in robustness and in case of occlusion.
Keywords: Camshift Algorithm, Computer Vision, Kalman Filter, Object tracking.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1319494 Performance Improvement of Moving Object Recognition and Tracking Algorithm using Parallel Processing of SURF and Optical Flow
Authors: Jungho Choi, Youngwan Cho
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The paper proposes a way of parallel processing of SURF and Optical Flow for moving object recognition and tracking. The object recognition and tracking is one of the most important task in computer vision, however disadvantage are many operations cause processing speed slower so that it can-t do real-time object recognition and tracking. The proposed method uses a typical way of feature extraction SURF and moving object Optical Flow for reduce disadvantage and real-time moving object recognition and tracking, and parallel processing techniques for speed improvement. First analyse that an image from DB and acquired through the camera using SURF for compared to the same object recognition then set ROI (Region of Interest) for tracking movement of feature points using Optical Flow. Secondly, using Multi-Thread is for improved processing speed and recognition by parallel processing. Finally, performance is evaluated and verified efficiency of algorithm throughout the experiment.Keywords: moving object recognition, moving object tracking, SURF, Optical Flow, Multi-Thread.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2632493 Multiple Object Tracking using Particle Swarm Optimization
Authors: Chen-Chien Hsu, Guo-Tang Dai
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This paper presents a particle swarm optimization (PSO) based approach for multiple object tracking based on histogram matching. To start with, gray-level histograms are calculated to establish a feature model for each of the target object. The difference between the gray-level histogram corresponding to each particle in the search space and the target object is used as the fitness value. Multiple swarms are created depending on the number of the target objects under tracking. Because of the efficiency and simplicity of the PSO algorithm for global optimization, target objects can be tracked as iterations continue. Experimental results confirm that the proposed PSO algorithm can rapidly converge, allowing real-time tracking of each target object. When the objects being tracked move outside the tracking range, global search capability of the PSO resumes to re-trace the target objects.Keywords: multiple object tracking, particle swarm optimization, gray-level histogram, image
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4087492 Fast and Robust Long-term Tracking with Effective Searching Model
Authors: Thang V. Kieu, Long P. Nguyen
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Kernelized Correlation Filter (KCF) based trackers have gained a lot of attention recently because of their accuracy and fast calculation speed. However, this algorithm is not robust in cases where the object is lost by a sudden change of direction, being obscured or going out of view. In order to improve KCF performance in long-term tracking, this paper proposes an anomaly detection method for target loss warning by analyzing the response map of each frame, and a classification algorithm for reliable target re-locating mechanism by using Random fern. Being tested with Visual Tracker Benchmark and Visual Object Tracking datasets, the experimental results indicated that the precision and success rate of the proposed algorithm were 2.92 and 2.61 times higher than that of the original KCF algorithm, respectively. Moreover, the proposed tracker handles occlusion better than many state-of-the-art long-term tracking methods while running at 60 frames per second.
Keywords: Correlation filter, long-term tracking, random fern, real-time tracking.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 759491 The Performance Improvement of the Target Position Determining System in Laser Tracking Based on 4Q Detector using Neural Network
Authors: A. Salmanpour, Sh. Mohammad Nejad
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One of the methods for detecting the target position error in the laser tracking systems is using Four Quadrant (4Q) detectors. If the coordinates of the target center is yielded through the usual relations of the detector outputs, the results will be nonlinear, dependent on the shape, target size and its position on the detector screen. In this paper we have designed an algorithm with using neural network that coordinates of the target center in laser tracking systems is calculated by using detector outputs obtained from visual modeling. With this method, the results except from the part related to the detector intrinsic limitation, are linear and dependent from the shape and target size.Keywords: four quadrant detector, laser tracking system, rangefinder, tracking sensor
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2194490 Video-Based Tracking of Laparoscopic Instruments Using an Orthogonal Webcams System
Authors: Fernando Pérez, Humberto Sossa, Rigoberto Martínez, Daniel Lorias, Arturo Minor
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This paper presents a system for tracking the movement of laparoscopic instruments which is based on an orthogonal system of webcams and video image processing. The movements are captured with two webcams placed orthogonally inside of the physical trainer. On the image, the instruments were detected by using color markers placed on the distal tip of each instrument. The 3D position of the tip of the instrument within the work space was obtained by linear triangulation method. Preliminary results showed linearity and repeatability in the motion tracking with a resolution of 0.616 mm in each axis; the accuracy of the system showed a 3D instrument positioning error of 1.009 ± 0.101 mm. This tool is a portable and low-cost alternative to traditional tracking devices and a trustable method for the objective evaluation of the surgeon’s surgical skills.
Keywords: Laparoscopic Surgery, Orthogonal Vision, Tracking Instruments, Triangulation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2622489 Driver Fatigue State Recognition with Pixel Based Caveat Scheme Using Eye-Tracking
Authors: K. Thulasimani, K. G. Srinivasagan
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Driver fatigue is an important factor in the increasing number of road accidents. Dynamic template matching method was proposed to address the problem of real-time driver fatigue detection system based on eye-tracking. An effective vision based approach was used to analyze the driver’s eye state to detect fatigue. The driver fatigue system consists of Face detection, Eye detection, Eye tracking, and Fatigue detection. Initially frames are captured from a color video in a car dashboard and transformed from RGB into YCbCr color space to detect the driver’s face. Canny edge operator was used to estimating the eye region and the locations of eyes are extracted. The extracted eyes were considered as a template matching for eye tracking. Edge Map Overlapping (EMO) and Edge Pixel Count (EPC) matching function were used for eye tracking which is used to improve the matching accuracy. The pixel of eyeball was tracked from the eye regions which are used to determine the fatigue state of the driver.Keywords: Driver fatigue detection, Driving safety, Eye tracking, Intelligent transportation system, Template matching.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1720488 Eye Tracking: Biometric Evaluations of Instructional Materials for Improved Learning
Authors: Janet Holland
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Eye tracking is a great way to triangulate multiple data sources for deeper, more complete knowledge of how instructional materials are really being used and emotional connections made. Using sensor based biometrics provides a detailed local analysis in real time expanding our ability to collect science based data for a more comprehensive level of understanding, not previously possible, for teaching and learning. The knowledge gained will be used to make future improvements to instructional materials, tools, and interactions. The literature has been examined and a preliminary pilot test was implemented to develop a methodology for research in Instructional Design and Technology. Eye tracking now offers the addition of objective metrics obtained from eye tracking and other biometric data collection with analysis for a fresh perspective.Keywords: Area of interest, eye tracking, biometrics, fixation, fixation count, fixation sequence, fixation time, gaze points, heat map, saccades, time to first fixation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 866487 GSM Position Tracking using a Kalman Filter
Authors: Jean-Pierre Dubois, Jihad S. Daba, M. Nader, C. El Ferkh
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GSM has undoubtedly become the most widespread cellular technology and has established itself as one of the most promising technology in wireless communication. The next generation of mobile telephones had also become more powerful and innovative in a way that new services related to the user-s location will arise. Other than the 911 requirements for emergency location initiated by the Federal Communication Commission (FCC) of the United States, GSM positioning can be highly integrated in cellular communication technology for commercial use. However, GSM positioning is facing many challenges. Issues like accuracy, availability, reliability and suitable cost render the development and implementation of GSM positioning a challenging task. In this paper, we investigate the optimal mobile position tracking means. We employ an innovative scheme by integrating the Kalman filter in the localization process especially that it has great tracking characteristics. When tracking in two dimensions, Kalman filter is very powerful due to its reliable performance as it supports estimation of past, present, and future states, even when performing in unknown environments. We show that enhanced position tracking results is achieved when implementing the Kalman filter for GSM tracking.Keywords: Cellular communication, estimation, GSM, Kalman filter, positioning
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3062486 Maximum Power Point Tracking by ANN Controller for a Standalone Photovoltaic System
Authors: K. Ranjani, M. Raja, B. Anitha
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In this paper, ANN controller for maximum power point tracking of photovoltaic (PV) systems is proposed and PV modeling is discussed. Maximum power point tracking (MPPT) methods are used to maximize the PV array output power by tracking continuously the maximum power point. ANN controller with hill-climbing algorithm offers fast and accurate converging to the maximum operating point during steady-state and varying weather conditions compared to conventional hill-climbing. The proposed algorithm gives a good maximum power operation of the PV system. Simulation results obtained are presented and compared with the conventional hill-climbing algorithm. Simulation results show the effectiveness of the proposed technique.
Keywords: Artificial neural network (ANN), hill-climbing, maximum power-point tracking (MPPT), photovoltaic.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3144485 Design and Implementation of Cricket-based Location Tracking System
Authors: Byung Ki Kim, Ho Min Jung, Jae-Bong Yoo, Wan Yeon Lee, Chan Young Park, Young Woong Ko
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In this paper, we present a novel approach to location system under indoor environment. The key idea of our work is accurate distance estimation with cricket-based location system using A* algorithm. We also use magnetic sensor for detecting obstacles in indoor environment. Finally, we suggest how this system can be used in various applications such as asset tracking and monitoring.Keywords: Cricket, Indoor Location Tracking, Mobile Robot, Localization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2056484 Real Time Object Tracking in H.264/ AVC Using Polar Vector Median and Block Coding Modes
Authors: T. Kusuma, K. Ashwini
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This paper presents a real time video surveillance system which is capable of tracking multiple real time objects using Polar Vector Median (PVM) and Block Coding Modes (BCM) with Global Motion Compensation (GMC). This strategy works in the packed area and furthermore utilizes the movement vectors and BCM from the compressed bit stream to perform real time object tracking. We propose to do this in view of the neighboring Motion Vectors (MVs) using a method called PVM. Since GM adds to the object’s native motion, for accurate tracking, it is important to remove GM from the MV field prior to further processing. The proposed method is tested on a number of standard sequences and the results show its advantages over some of the current modern methods.
Keywords: Block coding mode, global motion compensation, object tracking, polar vector median, video surveillance.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 739483 Lyapunov-Based Tracking Control for Nonholonomic Wheeled Mobile Robot
Authors: Raouf Fareh, Maarouf Saad, Sofiane Khadraoui, Tamer Rabie
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This paper presents a tracking control strategy based on Lyapunov approach for nonholonomic wheeled mobile robot. This control strategy consists of two levels. First, a kinematic controller is developed to adjust the right and left wheel velocities. Using this velocity control law, the stability of the tracking error is guaranteed using Lyapunov approach. This kinematic controller cannot be generated directly by the motors. To overcome this problem, the second level of the controllers, dynamic control, is designed. This dynamic control law is developed based on Lyapunov theory in order to track the desired trajectories of the mobile robot. The stability of the tracking error is proved using Lupunov and Barbalat approaches. Simulation results on a nonholonomic wheeled mobile robot are given to demonstrate the feasibility and effectiveness of the presented approach.Keywords: Mobile robot, trajectory tracking, Lyapunov, stability.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2373482 Comparison of Stationary and Two-Axis Tracking System of 50MW Photovoltaic Power Plant in Al-Kufra, Libya: Landscape Impact and Performance
Authors: Yasser Aldali
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The scope of this paper is to evaluate and compare the potential of LS-PV(Large Scale Photovoltaic Power Plant) power generation systems in the southern region of Libya at Al-Kufra for both stationary and tracking systems. A Microsoft Excel-VBA program has been developed to compute slope radiation, dew-point, sky temperature, and then cell temperature, maximum power output and module efficiency of the system for stationary system and for tracking system. The results for energy production show that the total energy output is 114GWh/year for stationary system and 148GWh/year for tracking system. The average module efficiency for the stationary system is 16.6% and 16.2% for the tracking system.
The values of electricity generation capacity factor (CF) and solar capacity factor (SCF) for stationary system were found to be 26% and 62.5% respectively and 34% and 82% for tracking system. The GCR (Ground Cover Ratio) for a stationary system is 0.7, which corresponds to a tilt angle of 24°. The GCR for tracking system was found to be 0.12. The estimated ground area needed to build a 50MW PV plant amounts to approx. 0.55km2 for a stationary PV field constituted by HIT PV arrays and approx. 91MW/ km2. In case of a tracker PV field, the required ground area amounts approx.2.4km2 and approx. 20.5MW/ km2.
Keywords: Large PV power plant, solar energy, environmental impact, Dual-axis tracking system, stationary system.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3091481 Planar Tracking Control of an Underactuated Autonomous Underwater Vehicle
Authors: Santhakumar M., Asokan T.
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This paper addresses the problem of trajectory tracking control of an underactuated autonomous underwater vehicle (AUV) in the horizontal plane. The underwater vehicle under consideration is not actuated in the sway direction, and the system matrices are not assumed to be diagonal and linear, as often found in the literature. In addition, the effect of constant bias of environmental disturbances is considered. Using backstepping techniques and the tracking error dynamics, the system states are stabilized by forcing the tracking errors to an arbitrarily small neighborhood of zero. The effectiveness of the proposed control method is demonstrated through numerical simulations. Simulations are carried out for an experimental vehicle for smooth, inertial, two dimensional (2D) reference trajectories such as constant velocity trajectory (a circle maneuver – constant yaw rate), and time varying velocity trajectory (a sinusoidal path – sinusoidal yaw rate).Keywords: autonomous underwater vehicle, system matrices, tracking control, time – varying feed back, underactuated control.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2131480 Increasing Lifetime of Target Tracking Wireless Sensor Networks
Authors: Khin Thanda Soe
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A model to identify the lifetime of target tracking wireless sensor network is proposed. The model is a static clusterbased architecture and aims to provide two factors. First, it is to increase the lifetime of target tracking wireless sensor network. Secondly, it is to enable good localization result with low energy consumption for each sensor in the network. The model consists of heterogeneous sensors and each sensing member node in a cluster uses two operation modes–active mode and sleep mode. The performance results illustrate that the proposed architecture consumes less energy and increases lifetime than centralized and dynamic clustering architectures, for target tracking sensor network.Keywords: Network lifetime, Target Localization, TargetTracking, Wireless Sensor Networks.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1715479 A Robust Method for Hand Tracking Using Mean-shift Algorithm and Kalman Filter in Stereo Color Image Sequences
Authors: Mahmoud Elmezain, Ayoub Al-Hamadi, Robert Niese, Bernd Michaelis
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Real-time hand tracking is a challenging task in many computer vision applications such as gesture recognition. This paper proposes a robust method for hand tracking in a complex environment using Mean-shift analysis and Kalman filter in conjunction with 3D depth map. The depth information solve the overlapping problem between hands and face, which is obtained by passive stereo measuring based on cross correlation and the known calibration data of the cameras. Mean-shift analysis uses the gradient of Bhattacharyya coefficient as a similarity function to derive the candidate of the hand that is most similar to a given hand target model. And then, Kalman filter is used to estimate the position of the hand target. The results of hand tracking, tested on various video sequences, are robust to changes in shape as well as partial occlusion.Keywords: Computer Vision and Image Analysis, Object Tracking, Gesture Recognition.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2899478 A Hybrid CamShift and l1-Minimization Video Tracking Algorithm
Authors: Clark Van Dam, Gagan Mirchandani
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The Continuously Adaptive Mean-Shift (CamShift) algorithm, incorporating scene depth information is combined with the l1-minimization sparse representation based method to form a hybrid kernel and state space-based tracking algorithm. We take advantage of the increased efficiency of the former with the robustness to occlusion property of the latter. A simple interchange scheme transfers control between algorithms based upon drift and occlusion likelihood. It is quantified by the projection of target candidates onto a depth map of the 2D scene obtained with a low cost stereo vision webcam. Results are improved tracking in terms of drift over each algorithm individually, in a challenging practical outdoor multiple occlusion test case.Keywords: CamShift, l1-minimization, particle filter, stereo vision, video tracking.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2036477 A Novel Prostate Segmentation Algorithm in TRUS Images
Authors: Ali Rafiee, Ahad Salimi, Ali Reza Roosta
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Prostate cancer is one of the most frequent cancers in men and is a major cause of mortality in the most of countries. In many diagnostic and treatment procedures for prostate disease accurate detection of prostate boundaries in transrectal ultrasound (TRUS) images is required. This is a challenging and difficult task due to weak prostate boundaries, speckle noise and the short range of gray levels. In this paper a novel method for automatic prostate segmentation in TRUS images is presented. This method involves preprocessing (edge preserving noise reduction and smoothing) and prostate segmentation. The speckle reduction has been achieved by using stick filter and top-hat transform has been implemented for smoothing. A feed forward neural network and local binary pattern together have been use to find a point inside prostate object. Finally the boundary of prostate is extracted by the inside point and an active contour algorithm. A numbers of experiments are conducted to validate this method and results showed that this new algorithm extracted the prostate boundary with MSE less than 4.6% relative to boundary provided manually by physicians.
Keywords: Prostate segmentation, stick filter, neural network, active contour.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1958476 Performance Comparison between ĆUK and SEPIC Converters for Maximum Power Point Tracking Using Incremental Conductance Technique in Solar Power Applications
Authors: James Dunia, Bakari M. M. Mwinyiwiwa
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Photovoltaic (PV) energy is one of the most important energy resources since it is clean, pollution free, and endless. Maximum Power Point Tracking (MPPT) is used in photovoltaic (PV) systems to maximize the photovoltaic output power, irrespective the variations of temperature and radiation conditions. This paper presents a comparison between Ćuk and SEPIC converter in maximum power point tracking (MPPT) of photovoltaic (PV) system. In the paper, advantages and disadvantages of both converters are described. Incremental conductance control method has been used as maximum power point tracking (MPPT) algorithm. The two converters and MPPT algorithm were modelled using MATLAB/Simulink software for simulation. Simulation results show that both Ćuk and SEPIC converters can track the maximum power point with some minor variations.
Keywords: Ćuk Converter, Incremental Conductance, Maximum Power Point Tracking, PV Module, SEPIC Converter.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 10208475 Adaptive Extended Kalman Filter for Ballistic Missile Tracking
Authors: Gaurav Kumar, Dharmbir Prasad, Rudra Pratap Singh
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In the current work, adaptive extended Kalman filter (AEKF) is presented for solution of ground radar based ballistic missile (BM) tracking problem in re-entry phase with unknown ballistic coefficient. The estimation of trajectory of any BM in re-entry phase is extremely difficult, because of highly non-linear motion of BM. The estimation accuracy of AEKF has been tested for a typical test target tracking problem adopted from literature. Further, the approach of AEKF is compared with extended Kalman filter (EKF). The simulation result indicates the superiority of the AEKF in solving joint parameter and state estimation problems.Keywords: Adaptive, AEKF, ballistic missile, EKF, re-entry phase, target tracking.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1641474 Motion-Based Detection and Tracking of Multiple Pedestrians
Authors: A. Harras, A. Tsuji, K. Terada
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Tracking of moving people has gained a matter of great importance due to rapid technological advancements in the field of computer vision. The objective of this study is to design a motion based detection and tracking multiple walking pedestrians randomly in different directions. In our proposed method, Gaussian mixture model (GMM) is used to determine moving persons in image sequences. It reacts to changes that take place in the scene like different illumination; moving objects start and stop often, etc. Background noise in the scene is eliminated through applying morphological operations and the motions of tracked people which is determined by using the Kalman filter. The Kalman filter is applied to predict the tracked location in each frame and to determine the likelihood of each detection. We used a benchmark data set for the evaluation based on a side wall stationary camera. The actual scenes from the data set are taken on a street including up to eight people in front of the camera in different two scenes, the duration is 53 and 35 seconds, respectively. In the case of walking pedestrians in close proximity, the proposed method has achieved the detection ratio of 87%, and the tracking ratio is 77 % successfully. When they are deferred from each other, the detection ratio is increased to 90% and the tracking ratio is also increased to 79%.
Keywords: Automatic detection, tracking, pedestrians.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 822473 A Vehicular Visual Tracking System Incorporating Global Positioning System
Authors: Hsien-Chou Liao, Yu-Shiang Wang
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Surveillance system is widely used in the traffic monitoring. The deployment of cameras is moving toward a ubiquitous camera (UbiCam) environment. In our previous study, a novel service, called GPS-VT, was firstly proposed by incorporating global positioning system (GPS) and visual tracking techniques for the UbiCam environment. The first prototype is called GODTA (GPS-based Moving Object Detection and Tracking Approach). For a moving person carried GPS-enabled mobile device, he can be tracking when he enters the field-of-view (FOV) of a camera according to his real-time GPS coordinate. In this paper, GPS-VT service is applied to the tracking of vehicles. The moving speed of a vehicle is much faster than a person. It means that the time passing through the FOV is much shorter than that of a person. Besides, the update interval of GPS coordinate is once per second, it is asynchronous with the frame rate of the real-time image. The above asynchronous is worsen by the network transmission delay. These factors are the main challenging to fulfill GPS-VT service on a vehicle.In order to overcome the influence of the above factors, a back-propagation neural network (BPNN) is used to predict the possible lane before the vehicle enters the FOV of a camera. Then, a template matching technique is used for the visual tracking of a target vehicle. The experimental result shows that the target vehicle can be located and tracking successfully. The success location rate of the implemented prototype is higher than that of the previous GODTA.Keywords: visual surveillance, visual tracking, globalpositioning system, intelligent transportation system
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1907472 Multi-Sensor Target Tracking Using Ensemble Learning
Authors: Bhekisipho Twala, Mantepu Masetshaba, Ramapulana Nkoana
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Multiple classifier systems combine several individual classifiers to deliver a final classification decision. However, an increasingly controversial question is whether such systems can outperform the single best classifier, and if so, what form of multiple classifiers system yields the most significant benefit. Also, multi-target tracking detection using multiple sensors is an important research field in mobile techniques and military applications. In this paper, several multiple classifiers systems are evaluated in terms of their ability to predict a system’s failure or success for multi-sensor target tracking tasks. The Bristol Eden project dataset is utilised for this task. Experimental and simulation results show that the human activity identification system can fulfil requirements of target tracking due to improved sensors classification performances with multiple classifier systems constructed using boosting achieving higher accuracy rates.
Keywords: Single classifier, machine learning, ensemble learning, multi-sensor target tracking.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 581471 Tracking Control of a Linear Parabolic PDE with In-domain Point Actuators
Authors: Amir Badkoubeh, Guchuan Zhu
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This paper addresses the problem of asymptotic tracking control of a linear parabolic partial differential equation with indomain point actuation. As the considered model is a non-standard partial differential equation, we firstly developed a map that allows transforming this problem into a standard boundary control problem to which existing infinite-dimensional system control methods can be applied. Then, a combination of energy multiplier and differential flatness methods is used to design an asymptotic tracking controller. This control scheme consists of stabilizing state-feedback derived from the energy multiplier method and feed-forward control based on the flatness property of the system. This approach represents a systematic procedure to design tracking control laws for a class of partial differential equations with in-domain point actuation. The applicability and system performance are assessed by simulation studies.Keywords: Tracking Control, In-domain point actuation, PartialDifferential Equations.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2046470 Model-Based Person Tracking Through Networked Cameras
Authors: Kyoung-Mi Lee, Youn-Mi Lee
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This paper proposes a way to track persons by making use of multiple non-overlapping cameras. Tracking persons on multiple non-overlapping cameras enables data communication among cameras through the network connection between a camera and a computer, while at the same time transferring human feature data captured by a camera to another camera that is connected via the network. To track persons with a camera and send the tracking data to another camera, the proposed system uses a hierarchical human model that comprises a head, a torso, and legs. The feature data of the person being modeled are transferred to the server, after which the server sends the feature data of the human model to the cameras connected over the network. This enables a camera that captures a person's movement entering its vision to keep tracking the recognized person with the use of the feature data transferred from the server.
Keywords: Person tracking, human model, networked cameras, vision-based surveillance.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1481469 Determination of Neighbor Node in Consideration of the Imaging Range of Cameras in Automatic Human Tracking System
Authors: Kozo Tanigawa, Tappei Yotsumoto, Kenichi Takahashi, Takao Kawamura, Kazunori Sugahara
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A automatic human tracking system using mobile agent technology is realized because a mobile agent moves in accordance with a migration of a target person. In this paper, we propose a method for determining the neighbor node in consideration of the imaging range of cameras.
Keywords: Human tracking, Mobile agent, Pan/Tilt/Zoom, Neighbor relation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1668