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Dynamic Scene Analysis in a Camera Network by Dr. Amit K. Roy-Chowdhury Ph.D. (Electrical & Computer Engineering), Center for Automation Research, University of Maryland, MD, USA 2002 on Monday, January 14, 2008 11:00am – 12:00pm, A265 Bourns Hall Abstract: As cameras get cheaper, large numbers of them are being installed in many applications. However, most of them transmit their videos to a central location where they are interpreted by human observers. This is infeasible as the number of cameras get larger. Therefore, it is very important to automatically extract meaningful patterns of dynamic events from the video sequences observed over the network. In this talk, we will start with a high-level presentation of the multi-camera networks that we are building at UCR. Thereafter, I will highlight the main issues that need to be addressed for this endeavor to be successful and focus on some of them. Specifically, I will describe two new results: (i) an appearance manifold of objects that is derived using a combination of analytically derived geometrical models and statistical data analysis, (ii) a closed-loop tracking framework that can track people through different activities. I will conclude by giving an overview of some ongoing research in this area. About the speaker: Dr. Amit K. Roy-Chowdhury is an Assistant Professor of Electrical Engineering and a Cooperating Faculty in the Dept. of Computer Science at the University of California, Riverside. He completed his PhD in 2002 from the University of Maryland, College Park, where he also worked as a Research Associate in 2003. Previous to that, he received his Masters in Systems Science and Automation from the Indian Institute of Science, Bangalore. His research interests are in the broad areas of image processing and analysis, computer vision, video communications and statistical methods for signal processing, pattern recognition and machine learning. Currently, he is working on problems of robust object recognition by integrating geometry and statistics, event analysis in large video networks, biological video analysis and multi-terminal video compression. His work is supported by grants from the National Science Foundation, Dept. of Defense, and private industries. Dr. Roy-Chowdhury has over sixty papers in peer-reviewed journals, conferences and edited books. He is an author of the book titled "Recognition of Humans and Their Activities Using Video". He is on the program committee of many major conferences in computer vision and image/signal processing and is a regular reviewer for the main journals in these areas. He is an Associate Editor of the IAPR journal Machine Vision and Applications and is on the organizing committees of CVPR 2008 and ICIP 2008. Dr. Roy-Chowdhury is conducting research on video sequence analysis for recognition, retrieval and communication, modeling of human activities from video sequences and robust estimation of accurate 3D models from video sequences. He is also interested in theoretical analysis of vision algorithms. He was a recipient of the National Talent Scholarship (Govt. of India), Graduate Fellowship (Govt. of India) and undergraduate (India) and graduate (UMD) student awards. Dynamic Scene Analysis in a Camera Network by Dr. Amit K. Roy-Chowdhury Ph.D. (Electrical & Computer Engineering), Center for Automation Research, University of Maryland, MD, USA 2002 on Monday, January 14, 2008 11:00am – 12:00pm, A265 Bourns Hall Abstract: As cameras get cheaper, large numbers of them are being installed in many applications. However, most of them transmit their videos to a central location where they are interpreted by human observers. This is infeasible as the number of cameras get larger. Therefore, it is very important to automatically extract meaningful patterns of dynamic events from the video sequences observed over the network. In this talk, we will start with a high-level presentation of the multi-camera networks that we are building at UCR. Thereafter, I will highlight the main issues that need to be addressed for this endeavor to be successful and focus on some of them. Specifically, I will describe two new results: (i) an appearance manifold of objects that is derived using a combination of analytically derived geometrical models and statistical data analysis, (ii) a closed-loop tracking framework that can track people through different activities. I will conclude by giving an overview of some ongoing research in this area. About the speaker: Dr. Amit K. Roy-Chowdhury is an Assistant Professor of Electrical Engineering and a Cooperating Faculty in the Dept. of Computer Science at the University of California, Riverside. He completed his PhD in 2002 from the University of Maryland, College Park, where he also worked as a Research Associate in 2003. Previous to that, he received his Masters in Systems Science and Automation from the Indian Institute of Science, Bangalore. His research interests are in the broad areas of image processing and analysis, computer vision, video communications and statistical methods for signal processing, pattern recognition and machine learning. Currently, he is working on problems of robust object recognition by integrating geometry and statistics, event analysis in large video networks, biological video analysis and multi-terminal video compression. His work is supported by grants from the National Science Foundation, Dept. of Defense, and private industries. Dr. Roy-Chowdhury has over sixty papers in peer-reviewed journals, conferences and edited books. He is an author of the book titled "Recognition of Humans and Their Activities Using Video". He is on the program committee of many major conferences in computer vision and image/signal processing and is a regular reviewer for the main journals in these areas. He is an Associate Editor of the IAPR journal Machine Vision and Applications and is on the organizing committees of CVPR 2008 and ICIP 2008. Dr. Roy-Chowdhury is conducting research on video sequence analysis for recognition, retrieval and communication, modeling of human activities from video sequences and robust estimation of accurate 3D models from video sequences. He is also interested in theoretical analysis of vision algorithms. He was a recipient of the National Talent Scholarship (Govt. of India), Graduate Fellowship (Govt. of India) and undergraduate (India) and graduate (UMD) student awards. |
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