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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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 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 |
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Uncontrolled Keywords: | Human actions, relevance feedback, spatiotemporal localization, video retrieval |
Subjects: | G400 Computer Science |
Department: | Faculties > Engineering and Environment > Computer and Information Sciences |
Related URLs: | |
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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