AUTOMATIC MOVING OBJECT DETECTION USING MOTION AND COLOR FEATURES
Abstract
This paper deals with the implementation of automatic detection of objects using hybrid parameters like motion and color features which are inevitable in various computer based vision applications like video surveillance system. We are using the hybrid parameters for detection on Background subtraction technique with the help of integration of new methods into real time object tracking system, followed by statistical optimization steps to increase high accuracy using high resolution image. MATLAB functions are used to create a basic image processor having different features like Red, Blue and Green components of color image and various other features (noise addition, removal, edge detection, cropping, resizing etc.) that is used in basic image edition and the result is displayed on the GUI platform.
References
[8] S. Pundlik and S. Birchfield, “Motion segmentation at any speed,” Proc. of the British Machine Vision Conf., 2006. [9] A. Aggarwal, S. Biswas, S. Singh, S. Sural, and A.K. Majumdar, "Object Tracking Using Background Subtraction and Motion Estimation in MPEG Videos," ACCV 2006, LNCS, vol. 3852, pp. 121130, Springer, Heidelberg (2006). [10] W. Zeng, J. Du, W. Gao, and Q. Huang, “Robust moving object segmentation on H.264|AVC compressed video using the block-based MRF model,” Real-Time Imaging, vol. 11(4), 2005, pp.290299. [11] W. You, M.S. Houari Sabirin, and M.Kim, "Realtime Detection and Tracking of Multiple Objects with Partial Decoding in H.264|AVC Bitstream Domain", in The 21st Annual IS&T/SPIE Symposium on Electronic Imaging, January 2009.
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