Toward Coherent Object Detection And Scene Layout Understanding

Detecting objects in complex scenes while recovering the scene layout is a critical functionality in many vision-based applications. Inspired by the work of [18], we advocate the importance of geometric contextual reasoning for object recognition. We start from the intuition that objects' location and pose in the 3D space are not arbitrarily distributed but rather constrained by the fact that objects must lie on one or multiple supporting surfaces. We model such supporting surfaces by means of hidden parameters (i.e. not explicitly observed) and formulate the problem of joint scene reconstruction and object recognition as the one of finding the set of parameters that maximizes the joint probability of having a number of detected objects on K supporting planes given the observations. As a key ingredient for solving this optimization problem, we have demonstrated a novel relationship between object location and pose in the image, and the scene layout parameters (i.e. normal of one ...

• Type: Conference
• Year: 2010
• Where: CVPR
• Authors: Yingze Bao, Min Sun, Silvio Savarese
• Keywords: Computer Vision, CVPR 2010, Object Recognition, Scene Layout, Supporting Surfaces