Object-Specific Figure-Ground Segregation

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.

• Type: Conference
• Year: 2003
• Where: CVPR
• Authors: Stella X. Yu, Jianbo Shi
• Keywords: Computer Vision, Constrained Eigenvalue Problem, CVPR 2003, Edge Detection, Joint Grouping Criterion, Low-level Pixel Grouping