Efficient video segmentation using temporally updated mean shift clustering

Nemanja Petrović; Ljubomir Jovanov; Aleksandra Pižurica; Wilfried Philips

doi:10.1117/12.792998

15 September 2008 Efficient video segmentation using temporally updated mean shift clustering

Nemanja Petrović, Ljubomir Jovanov, Aleksandra Pižurica, Wilfried Philips

Proceedings Volume 7073, Applications of Digital Image Processing XXXI; 70731R (2008) https://doi.org/10.1117/12.792998
Event: Optical Engineering + Applications, 2008, San Diego, California, United States

Abstract

This paper presents a new method for unsupervised video segmentation based on mean shift clustering in spatio-temporal domain. The main novelties of the proposed approach are dynamic temporal adaptation of clusters due to which the segmentation evolves quickly and smoothly over time. The proposed method consists of a short initialization phase and an update phase. The proposed method significantly reduce the computation load for the mean shift clustering. In the update phase only the positions of relatively small number of cluster centers are updated and new frames are segmented based on the segmentation of previous frames. The method segments video in real-time and tracks video objects effectively.

Citation Download Citation

Nemanja Petrović, Ljubomir Jovanov, Aleksandra Pižurica, and Wilfried Philips "Efficient video segmentation using temporally updated mean shift clustering", Proc. SPIE 7073, Applications of Digital Image Processing XXXI, 70731R (15 September 2008); https://doi.org/10.1117/12.792998

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