Sciweavers

Share
ACCV
2009
Springer

Video Segmentation Using Iterated Graph Cuts Based on Spatio-temporal Volumes

9 years 6 months ago
Video Segmentation Using Iterated Graph Cuts Based on Spatio-temporal Volumes
Abstract. We present a novel approach to segmenting video using iterated graph cuts based on spatio-temporal volumes. We use the mean shift clustering algorithm to build the spatio-temporal volumes with different bandwidths from the input video. We compute the prior probability obtained by the likelihood from a color histogram and a distance transform using the segmentation results from graph cuts in the previous process, and set the probability as the t-link of the graph for the next process. The proposed method can segment regions of an object with a stepwise process from global to local segmentation by iterating the graph-cuts process with mean shift clustering using a different bandwidth. It is possible to reduce the number of nodes and edges to about 1/25 compared to the conventional method with the same segmentation rate.
Tomoyuki Nagahashi, Hironobu Fujiyoshi, Takeo Kana
Added 23 Jul 2010
Updated 23 Jul 2010
Type Conference
Year 2009
Where ACCV
Authors Tomoyuki Nagahashi, Hironobu Fujiyoshi, Takeo Kanade
Comments (0)
books