Shape Band: A Deformable Object Detection Approach

In this paper, we focus on the problem of detecting/ matching a query object in a given image. We propose a new algorithm, shape band, which models an object within a bandwidth of its sketch/contour. The features associated with each point on the sketch are the gradients within the bandwidth. In the detection stage, the algorithm simply scans an input image at various locations and scales for good candidates. We then perform fine scale shape matching to locate the precise object boundaries, also by taking advantage of the information from the shape band. The overall algorithm is very easy to implement, and our experimental results show that it can outperform stat-of-the-art contour based object detection algorithms.

• Type: Conference
• Year: 2009
• Where: CVPR
• Authors: Xiang Bai (Huazhong University of Science and Technology), Quannan Li (Huazhong University of Science and Technology), Longin Jan Latecki (Temple University), Wenyu Liu (Huazhong University of Science and Technology), Zhuowen Tu (UCLA)
• Keywords: Computer Vision, CVPR 2009, Deformable Object Detection