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Automatic Fast Video Object Detection and Tracking on Video Surveillance System


Affiliations
1 Department of Electronics and Communication Engineering, Einstein College of Engineering, India
2 Department of Electronics and Communication Engineering, Sri Vidya College of Engineering and Technology, India
3 Department of Electronics and Instrumentation Engineering, National Engineering College, India
     

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This paper describes the advance techniques for object detection and tracking in video. Most visual surveillance systems start with motion detection. Motion detection methods attempt to locate connected regions of pixels that represent the moving objects within the scene; different approaches include frame-to-frame difference, background subtraction and motion analysis. The motion detection can be achieved by Principle Component Analysis (PCA) and then separate an objects from background using background subtraction. The detected object can be segmented. Segmentation consists of two schemes: one for spatial segmentation and the other for temporal segmentation. Tracking approach can be done in each frame of detected Object. Pixel label problem can be alleviated by the MAP (Maximum a Posteriori) technique.

Keywords

Background Subtraction, Object Tracking, Principle Component Analysis, Spatio-Temporal Segmentation, MAP.
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  • Automatic Fast Video Object Detection and Tracking on Video Surveillance System

Abstract Views: 292  |  PDF Views: 0

Authors

V. Arunachalam
Department of Electronics and Communication Engineering, Einstein College of Engineering, India
I. Sorimuthu
Department of Electronics and Communication Engineering, Einstein College of Engineering, India
V. Rajagopal
Department of Electronics and Communication Engineering, Sri Vidya College of Engineering and Technology, India
B. Sankaragomathi
Department of Electronics and Instrumentation Engineering, National Engineering College, India

Abstract


This paper describes the advance techniques for object detection and tracking in video. Most visual surveillance systems start with motion detection. Motion detection methods attempt to locate connected regions of pixels that represent the moving objects within the scene; different approaches include frame-to-frame difference, background subtraction and motion analysis. The motion detection can be achieved by Principle Component Analysis (PCA) and then separate an objects from background using background subtraction. The detected object can be segmented. Segmentation consists of two schemes: one for spatial segmentation and the other for temporal segmentation. Tracking approach can be done in each frame of detected Object. Pixel label problem can be alleviated by the MAP (Maximum a Posteriori) technique.

Keywords


Background Subtraction, Object Tracking, Principle Component Analysis, Spatio-Temporal Segmentation, MAP.