Detection of change in video based on local pattern and photometric features

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with host publication)peer-review

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Author(s)

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Detail(s)

Original languageEnglish
Title of host publicationWSCG 2018 - Short Papers Proceedings
Subtitle of host publication26. International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision, WSCG 2018
EditorsVaclav Skala
Pages174-182
Publication statusPublished - 28 May 2018

Publication series

NameComputer Science Research Notes
PublisherUniversity of West Bohemia
Volume2802
ISSN (Print)2464-4617

Conference

Title26th International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision (WSCG 2018)
PlaceCzech Republic
CityPlzen
Period28 May - 1 June 2018

Abstract

The segmentation of moving objects in video can be formulated as a background subtraction problem – the detection of change in each image frame. The background scene is learned and modeled. A pixelwise process is employed to determine whether the current pixel is similar or not to the background model. The detection of change in video is challenging due to the non-stationary background such as illumination change, background motions, etc. We propose new features for background modeling. Perception-based local ternary patterns are generated from the same color channels as well as from different color channels. Features computed from the local patterns are stored in the background model as samples. If the current pixel is classified as background, the background model is updated. Finally, we propose a probabilistic refinement to improve each change region by taking into account the spatially consistency of image features. We compare our method with various background subtraction algorithms on some video datasets. Our method can achieve 13% better performance than other methods.

Research Area(s)

  • Background modeling, Change detection, Local ternary pattern, Cross-channel pattern, Probabilistic foreground refinement

Citation Format(s)

Detection of change in video based on local pattern and photometric features. / Chan, K L.
WSCG 2018 - Short Papers Proceedings: 26. International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision, WSCG 2018. ed. / Vaclav Skala. 2018. p. 174-182 (Computer Science Research Notes; Vol. 2802).

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with host publication)peer-review