DocumentCode :
3332603
Title :
A Video Representation Using Temporal Superpixels
Author :
Chang, Joana ; Donglai Wei ; Fisher, John W.
fYear :
2013
fDate :
23-28 June 2013
Firstpage :
2051
Lastpage :
2058
Abstract :
We develop a generative probabilistic model for temporally consistent super pixels in video sequences. In contrast to supermodel methods, object parts in different frames are tracked by the same temporal super pixel. We explicitly model flow between frames with a bilateral Gaussian process and use this information to propagate super pixels in an online fashion. We consider four novel metrics to quantify performance of a temporal super pixel representation and demonstrate superior performance when compared to supermodel methods.
Keywords :
Gaussian processes; image representation; image sequences; video signal processing; bilateral Gaussian process; generative probabilistic model; object parts; supervoxel methods; temporal superpixels; video representation; video sequences; Clustering algorithms; Graphical models; Image segmentation; Joints; Kernel; Motion segmentation; Topology; oversegmentation; superpixels; supervoxels; tracking; video segmentation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Vision and Pattern Recognition (CVPR), 2013 IEEE Conference on
Conference_Location :
Portland, OR
ISSN :
1063-6919
Type :
conf
DOI :
10.1109/CVPR.2013.267
Filename :
6619111
Link To Document :
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