Object recognition using junctions

  • Authors:

  • Bo Wang;Xiang Bai;Xinggang Wang;Wenyu Liu;Zhuowen Tu

  • Affiliations:

  • Dept. of Electronics and Information Engineering, Huazhong University of Science and Technology, China;Dept. of Electronics and Information Engineering, Huazhong University of Science and Technology, China;Dept. of Electronics and Information Engineering, Huazhong University of Science and Technology, China;Dept. of Electronics and Information Engineering, Huazhong University of Science and Technology, China;Lab of Neuro Imaging, University of California, Los Angeles

  • Venue:
  • ECCV'10 Proceedings of the 11th European conference on Computer vision: Part V
  • Year:
  • 2010

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Abstract

In this paper, we propose an object detection/recognition algorithm based on a new set of shape-driven features and morphological operators. Each object class is modeled by the corner points (junctions) on its contour. We design two types of shape-context like features between the corner points, which are efficient to compute and effective in capturing the underlying shape deformation. In the testing stage, we use a recently proposed junction detection algorithm [1] to detect corner points/junctions on natural images. The detection and recognition of an object are then done by matching learned shape features to those in the input image with an efficient search strategy. The proposed system is robust to a certain degree of scale change and we obtained encouraging results on the ETHZ dataset. Our algorithm also has advantages of recognizing object parts and dealing with occlusions.