Paper
28 April 2010 Activity based video indexing and search
Yang Chen, Qin Jiang, Swarup Medasani, David Allen, Tsai-ching Lu
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Abstract
We describe a method for searching videos in large video databases based on the activity contents present in the videos. Being able to search videos based on the contents (such as human activities) has many applications such as security, surveillance, and other commercial applications such as on-line video search. Conventional video content-based retrieval (CBR) systems are either feature based or semantics based, with the former trying to model the dynamics video contents using the statistics of image features, and the latter relying on automated scene understanding of the video contents. Neither approach has been successful. Our approach is inspired by the success of visual vocabulary of "Video Google" by Sivic and Zisserman, and the work of Nister and Stewenius who showed that building a visual vocabulary tree can improve the performance in both scalability and retrieval accuracy for 2-D images. We apply visual vocabulary and vocabulary tree approach to spatio-temporal video descriptors for video indexing, and take advantage of the discrimination power of these descriptors as well as the scalability of vocabulary tree for indexing. Furthermore, this approach does not rely on any model-based activity recognition. In fact, training of the vocabulary tree is done off-line using unlabeled data with unsupervised learning. Therefore the approach is widely applicable. Experimental results using standard human activity recognition videos will be presented that demonstrate the feasibility of this approach.
© (2010) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Yang Chen, Qin Jiang, Swarup Medasani, David Allen, and Tsai-ching Lu "Activity based video indexing and search", Proc. SPIE 7708, Mobile Multimedia/Image Processing, Security, and Applications 2010, 77080K (28 April 2010); https://doi.org/10.1117/12.850491
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KEYWORDS
Video

Video surveillance

Visualization

Databases

Semantic video

Image retrieval

Feature extraction

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