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Abstract
As digital video databases grow, so grows the problem of effectively navigating through them. In this paper we propose a novel content-based video retrieval approach to searching such video databases, specifically those involving human actions, incorporating spatio-temporal localization. We outline a novel, highly efficient localization model that first performs temporal localization based on histograms of evenly spaced time-slices, then spatial localization based on histograms of a 2-D spatial grid. We further argue that our retrieval model, based on the aforementioned localization, followed by relevance ranking, results in a highly discriminative system, while remaining an order of magnitude faster than the current state-of-the-art method. We also show how relevance feedback can be applied to our localization and ranking algorithms. As a result, the presented system is more directly applicable to real-world problems than any prior content-based video retrieval system.
Highlights
W ITH THE increased availability of digital video recording technology, more videos are being created than ever before, with these videos coming from diverse domains such as surveillance, amateur film-making, and home recording
We look at an alternative approach to this problem—content-based video retrieval (CBVR), which is an extension of content-based image retrieval (CBIR) to the video domain
We focus on searching human actions, which allows us to utilize the vast amount of prior human action recognition research
Summary
W ITH THE increased availability of digital video recording technology, more videos are being created than ever before, with these videos coming from diverse domains such as surveillance, amateur film-making, and home recording. These videos contribute to the growth of video media databases, such as those available online to consumers (e.g., YouTube), or CCTV footage collections. From this exponential growth rises a new problem: how can these vast collections of media be accessed in the most effective way, so that users can find what they are looking for?.
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