Efficient Search and Localization of Human Actions in Video Databases

Shao, Ling, Jones, Simon and Li, Xuelong (2014) Efficient Search and Localization of Human Actions in Video Databases. IEEE Transactions on Circuits and Systems for Video Technology, 24 (3). pp. 504-512. ISSN 1051-8215

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Official URL: http://dx.doi.org/10.1109/TCSVT.2013.2276700


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 stateof-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.

Item Type: Article
Uncontrolled Keywords: Human actions, relevance feedback, spatiotemporal localization, video retrieval
Subjects: G400 Computer Science
Department: Faculties > Engineering and Environment > Computer and Information Sciences
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Depositing User: Paul Burns
Date Deposited: 10 Jun 2015 13:28
Last Modified: 17 Dec 2023 16:48
URI: https://nrl.northumbria.ac.uk/id/eprint/22826

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