Object Detection and Segmentation from Joint Embedding of Parts and Pixels

We present a new framework in which image segmentation, figure/ground organization, and object detection all appear as the result of solving a single grouping problem. This framework serves as a perceptual organization stage that integrates information from low-level image cues with that of high-level part detectors. Pixels and parts each appear as nodes in a graph whose edges encode both affinity and ordering relationships. We derive a generalized eigenproblem from this graph and read off an interpretation of the image from the solution eigenvectors. Combining an off-the-shelf top-down part-based person detector with our low-level cues and grouping formulation, we demonstrate improvements to object detection and segmentation.

• Type: Journal
• Year: 2011
• Where: ICCV
• Authors: Michael Maire, Stella X. Yu, Pietro Perona
• Keywords: Computer Vision, ICCV 2011, Image Segmentation, Organization Stage, Perceptual Organization