Title :
Moving Object Segmentation Using Dynamic 3D Graph Cuts and GMM
Author :
Li, Bo ; Yuan, Baozong ; Sun, Yunda
Author_Institution :
Inst. of Inf. Sci., Beijing Jiaotong Univ.
Abstract :
It is one of the most challenging problems in computer vision how to segment moving objects accurately. In this paper, we present a novel approach to segment moving objects with edge information and temporal information using 3D graph cuts model when cameras is fixed. Moving object segmentation is modeled as finding a minimum energy of 3D graph. Our algorithm assigns n-links in 3D graph according to spatial gradient in same frame and temporal gradient in neighboring frames. Gaussian mixture model is used to assign t-links with edge difference term and shadow elimination term. Finally, a dynamic graph cuts algorithm is used to find the minimum cut of 3D graph and segments moving objects in image sequences. Experiments show that our approach achieves nice performance
Keywords :
Gaussian processes; computer graphics; image segmentation; image sequences; GMM; Gaussian mixture model; dynamic 3D graph cuts; edge difference term; frame gradient; image sequences; moving object segmentation; shadow elimination term; spatial gradient; temporal gradient; Cameras; Computer vision; Heuristic algorithms; Image segmentation; Image sequences; Information science; Object segmentation; Pixel; Sun; Surveillance;
Conference_Titel :
Signal Processing, 2006 8th International Conference on
Conference_Location :
Beijing
Print_ISBN :
0-7803-9736-3
Electronic_ISBN :
0-7803-9736-3
DOI :
10.1109/ICOSP.2006.345658
