Efficient extraction and representation of spatial information from video data

Hajar Sadeghi Sokeh, Stephen Gould, Jochen Renz

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    14 Citations (Scopus)

    Abstract

    Vast amounts of video data are available on the web and are being generated daily using surveillance cameras or other sources. Being able to efficiently analyse and process this data is essential for a number of different applications. We want to be able to efficiently detect activities in these videos or be able to extract and store essential information contained in these videos for future use and easy search and access. Cohn et al. (2012) proposed a comprehensive representation of spatial features that can be efficiently extracted from video and used for these purposes. In this paper, we present a modified version of this approach that is equally efficient and allows us to extract spatial information with much higher accuracy than previously possible. We present efficient algorithms both for extracting and storing spatial information from video, as well as for processing this information in order to obtain useful spatial features. We evaluate our approach and demonstrate that the extracted spatial information is considerably more accurate than that obtained from existing approaches.

    Original languageEnglish
    Title of host publicationIJCAI 2013 - Proceedings of the 23rd International Joint Conference on Artificial Intelligence
    Pages1076-1082
    Number of pages7
    Publication statusPublished - 2013
    Event23rd International Joint Conference on Artificial Intelligence, IJCAI 2013 - Beijing, China
    Duration: 3 Aug 20139 Aug 2013

    Publication series

    NameIJCAI International Joint Conference on Artificial Intelligence
    ISSN (Print)1045-0823

    Conference

    Conference23rd International Joint Conference on Artificial Intelligence, IJCAI 2013
    Country/TerritoryChina
    CityBeijing
    Period3/08/139/08/13

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