Stella X. Yu : Research

Object-Specific Figure-Ground Segregation
Stella X. YU and Jianbo SHI
Computer Vision and Pattern Recognition, Madison, Wisconsin, June 16-22, 2003.
We consider the problem of segmenting an image into foreground and background, with foreground containing solely objects of interest known a priori. We propose an integration model that incorporates both edge detection and object part detection results. It consists of two parallel processes: low-level pixel grouping and high-level patch grouping. We seek a solution that optimizes a joint grouping criterion in a reduced space enforced by grouping correspondence between pixels and patches. Using spectral graph partitioning, we show that a near global optimum can be found by solving a constrained eigenvalue problem. We report promising experimental results on a dataset of $15$ objects under clutter and occlusion.
image segmentation, figure-ground, object recognition, graph partitioning, constrained optimization