Automatic foreground extraction for images and videos

In this paper, an automatic foreground extraction algorithm for images and videos is presented. It first automatically locates the foreground object coarsely by a salience detection algorithm, and then refines the object by Weighted Kernel Density Estimation (WKDE) and graph cut algorithm. A new initial probability map construction algorithm for WKDE is also presented. We then extend our algorithm to videos by an opacity tracking algorithm. It can automatically extract the foreground with high accuracy even for the videos with non-static background. The experiments demonstrate the effectiveness of our approach.

[1]  Teofilo F. GONZALEZ,et al.  Clustering to Minimize the Maximum Intercluster Distance , 1985, Theor. Comput. Sci..

[2]  Chang-Su Kim,et al.  Real-time segmentation of objects from video sequences with non-stationary backgrounds using spatio-temporal coherence , 2008, 2008 15th IEEE International Conference on Image Processing.

[3]  Larry S. Davis,et al.  Iterative figure-ground discrimination , 2004, Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004..

[4]  Larry S. Davis,et al.  Improved fast gauss transform and efficient kernel density estimation , 2003, Proceedings Ninth IEEE International Conference on Computer Vision.

[5]  Zhi Liu,et al.  A Novel Video Object Tracking Approach Based on Kernel Density Estimation and Markov Random Field , 2007, 2007 IEEE International Conference on Image Processing.

[6]  Luc Vincent,et al.  Watersheds in Digital Spaces: An Efficient Algorithm Based on Immersion Simulations , 1991, IEEE Trans. Pattern Anal. Mach. Intell..

[7]  Nanning Zheng,et al.  Learning to Detect a Salient Object , 2011, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[8]  Harry Shum,et al.  Lazy snapping , 2004, ACM Trans. Graph..

[9]  A. Criminisi,et al.  Bilayer Segmentation of Live Video , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).

[10]  Takeshi Naemura,et al.  Real-Time Video Matting Based on Bilayer Segmentation , 2009, ACCV.