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Proceedings Paper

NeTra-V: toward an object-based video representation
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Paper Abstract

There is a growing need for new representations of video that allow not only compact storage of data but also content-based functionalities such as search and manipulation of objects. We present here a prototype system, called NeTra-V, that is currently being developed to address some of these content related issues. The system has a two-stage video processing structure: a global feature extraction and clustering stage, and a local feature extraction and object-based representation stage. Key aspects of the system include a new spatio-temporal segmentation and object-tracking scheme, and a hierarchical object-based video representation model. The spatio-temporal segmentation scheme combines the color/texture image segmentation and affine motion estimation techniques. Experimental results show that the proposed approach can handle large motion. The output of the segmentation, the alpha plane as it is referred to in the MPEG-4 terminology, can be used to compute local image properties. This local information forms the low-level content description module in our video representation. Experimental results illustrating spatio- temporal segmentation and tracking are provided.

Paper Details

Date Published: 23 December 1997
PDF: 12 pages
Proc. SPIE 3312, Storage and Retrieval for Image and Video Databases VI, (23 December 1997); doi: 10.1117/12.298443
Show Author Affiliations
Yining Deng, Univ. of California/Santa Barbara (United States)
Debargha Mukherjee, Univ. of California/Santa Barbara (United States)
B. S. Manjunath, Univ. of California/Santa Barbara (United States)


Published in SPIE Proceedings Vol. 3312:
Storage and Retrieval for Image and Video Databases VI
Ishwar K. Sethi; Ramesh C. Jain, Editor(s)

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