Video event detection based on over-segmented STV regions

Jing Wang, Zhijie Xu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Real-world environment introduces many variations into video recordings such as changing illumination and object dynamics. In this paper, a technique for abstracting useful spatio-temporal features from graph-based segmentation operations has been proposed. A spatio-temporal volume (STV)-based shape matching algorithm is then devised by using the intersection theory to facilitate the definition and detection of video events. To maintain system efficiency, this research has integrated an innovative feature-weight evaluation mechanism which rewards or punishes recognition outputs based on the segmentation quality. Substantial improvements on both the event Precision and Recall rate and the processing efficiency have been observed in the experiments in the project.

Original languageEnglish
Title of host publication2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops 2011)
PublisherIEEE Computer Society
Pages1464-1471
Number of pages8
ISBN (Electronic)9781467300636, 9781467300612
ISBN (Print)9781467300629
DOIs
Publication statusPublished - 2011
EventIEEE International Conference on Computer Vision Workshops, ICCV Workshops 2011 - Barcelona, Spain
Duration: 6 Nov 201113 Nov 2011

Conference

ConferenceIEEE International Conference on Computer Vision Workshops, ICCV Workshops 2011
CountrySpain
CityBarcelona
Period6/11/1113/11/11

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  • Cite this

    Wang, J., & Xu, Z. (2011). Video event detection based on over-segmented STV regions. In 2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops 2011) (pp. 1464-1471). [6130423] IEEE Computer Society. https://doi.org/10.1109/ICCVW.2011.6130423