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Distributed Tracking in Smart Camera Networks
, M.Sc. Thesis Sharif University of Technology ; Hossein Khalaj, Babak (Supervisor)
Abstract
Human tracking is an essential step in many computer vision-based applications. As single view tracking may not be sufficiently robust and accurate, tracking based on multiple cameras has been widely considered in recent years. This thesis presents a distributed human tracking method in a smart camera network and introduces a particle filter design based on Histogram of Oriented Gradients (HOG) and color histogram. The proposed adaptive motion model also estimates the target speed from the history of its latest displacement and improves the robustness of the tracker by decreasing the probability of missing targets. In addition, a distributed data fusion method is proposed which fuses the...
Multi-View Human Tracking With Uncalibrated Cameras
, M.Sc. Thesis Sharif University of Technology ; Kasaei, Shohreh (Supervisor)
Abstract
Human tracking is one of the most important research topics in computer vision with application in surveillance, crowd analysis, human motion and behavior analysis, and human-computer interaction. Availability of a large number of cameras has caused the need of designing automatic tracking methods. One of the most important challenges in automatic tracking is the occlusion of objects. Several methods have been proposed in the literature to solve this problem. One of the most popular and powerful methods is based on the usage of multiple views of the same scene in a cooperative manner between cameras. The most important challenge in using multiple cameras is the complexity of the tracker in...
A Vision-based Virtual Assistant. Case Study: Human Detection and Tracking on Surveillance Cameras
, M.Sc. Thesis Sharif University of Technology ; Bagheri Shouraki, Saeed (Supervisor) ; Mohammadzadeh, Hoda (Supervisor)
Abstract
This thesis suggests a practical system designed for the implementation of vision-based virtual assistants, aligning with the identified needs in the research background. Distinguishing itself from current literature, this study thoroughly explores and delineates the computing hierarchy while also suggesting the appropriate software architecture customized for the effective utilization of virtual assistants. Focusing on the most common application in vision-based virtual assistants—object detection and tracking—the research introduces an efficient multi-object tracking method using the tracking-by-detection paradigm. Notably, the proposed tracker stands out for its minimal computational...
Distibuted human tracking in smart camera networks by adaptive particle filtering and data fusion
, Article 2012 6th International Conference on Distributed Smart Cameras, ICDSC 2012, 30 October 2012 through 2 November 2012 ; November , 2012 ; 9781450317726 (ISBN) ; Khalaj, B. H ; Sharif University of Technology
2012
Abstract
Human tracking is an essential step in many computer vision-based applications. As single view tracking may not be sufficiently robust and accurate, tracking based on multiple cameras has been widely considered in recent years. This paper presents a distributed human tracking method in a smart camera network and introduces a particle filter design based on Histogram of Oriented Gradients (HOG) and color histogram. The proposed adaptive motion model also estimates the target speed from the history of its latest displacement and improves the robustness of the tracker by decreasing the probability of missing targets. In addition, a distributed data fusion method is proposed which fuses the...
A new Bayesian classifier for skin detection
, Article 3rd International Conference on Innovative Computing Information and Control, ICICIC'08, Dalian, Liaoning, 18 June 2008 through 20 June 2008 ; 2008 ; 9780769531618 (ISBN) ; Mousavi, M. E ; Sharif University of Technology
2008
Abstract
Skin detection has different applications in computer vision such as face detection, human tracking and adult content filtering. One of the major approaches in pixel based skin detection is using Bayesian classifiers. Bayesian classifiers performance is highly related to their training set. In this paper, we introduce a new Bayesian classifier skin detection method. The main contribution of this paper is creating a huge database to create color probability tables and new method for creating skin pixels data set. Our database consists of about 80000 images containing more than 5 billions pixels. Our tests shows that the performance of Bayesian classifier trained on our data set is better than...