Who Blocks Who: Simultaneous clothing segmentation for grouping images

  • Authors:
  • Nan Wang;Haizhou Ai

  • Affiliations:
  • Computer Science and Technology Department, Tsinghua University, Beijing, China;Computer Science and Technology Department, Tsinghua University, Beijing, China

  • Venue:
  • ICCV '11 Proceedings of the 2011 International Conference on Computer Vision
  • Year:
  • 2011

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Abstract

Clothing is one of the most informative cues of human appearance. In this paper, we propose a novel multi-person clothing segmentation algorithm for highly occluded images. The key idea is combining blocking models to address the person-wise occlusions. In contrary to the traditional layered model that tries to solve the full layer ranking problem, the proposed blocking model partitions the problem into a series of pair-wise ones and then determines the local blocking relationship based on individual and contextual information. Thus, it is capable of dealing with cases with a large number of people. Additionally, we propose a layout model formulated as Markov Network which incorporates the blocking relationship to pursue an approximately optimal clothing layout for group people. Experiments demonstrated on a group images dataset show the effectiveness of our algorithm.