(Publisher of Peer Reviewed Open Access Journals)

International Journal of Advanced Computer Research (IJACR)

ISSN (Print):2249-7277    ISSN (Online):2277-7970
Volume-3 Issue-10 June-2013
Full-Text PDF
Paper Title : Video Object Tracking based on Automatic Background Segmentation and updating using RBF neural network
Author Name : Pushpender Prasad Chaturvedi, Amit Singh Rajput, Aabha Jain
Abstract :

In this paper, the problems associated with the automatic object segmentation of the video sequences are considered. Towards this objective, a unique method that combines of image and video processing techniques ranged from noise filtering to data clustering is developed. The method also addresses a number of challenging issues along with computational complexity, accuracy, generality, and robustness. One of the primary aims of this paper is to find segmentation of color, texture, motion, shape, frame difference, and other methods of video segmentation for automatic detection considering the real-time processing requirements. In contrast to frame-wise tracking techniques, the employment of a spatiotemporal data that is constructed from multiple video frames introduces new degrees of freedom that can be exploited in terms of object extraction and content analysis. The current notions of region segmentation are extended to the spatiotemporal domain, and new models to estimate the object motion are derived.

Keywords : Video Processing, Wavelet, RBF.
Cite this article : Pushpender Prasad Chaturvedi, Amit Singh Rajput, Aabha Jain, " Video Object Tracking based on Automatic Background Segmentation and updating using RBF neural network " , International Journal of Advanced Computer Research (IJACR), Volume-3, Issue-10, June-2013 ,pp.86-90.