Object-Specific Figure-Ground Segregation
- Stella X. YU and Jianbo SHI
Computer Vision and Pattern Recognition,
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