Rotation Invariant Non-rigid Shape Matching in Cluttered Scenes

  • Wei Lian
  • Lei Zhang
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6315)


This paper presents a novel and efficient method for locating deformable shapes in cluttered scenes. The shapes to be detected may undergo arbitrary translational and rotational changes, and they can be non-rigidly deformed, occluded and corrupted by clutters. All these problems make the accurate and robust shape matching very difficult. By using a new shape representation, which involves a powerful feature descriptor, the proposed method can overcome the above difficulties successfully, and it possesses the property of global optimality. The experiments on both synthetic and real data validated that the proposed algorithm is robust to various types of disturbances. It can robustly detect the desired shapes in complex and highly cluttered scenes.


Rotation Invariant Point Match Viterbi Algorithm Point Correspondence Rest Point 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Wei Lian
    • 1
  • Lei Zhang
    • 2
  1. 1.Dept. of Computer ScienceChangzhi UniversityChangzhiChina
  2. 2.Biometric Research Center, Dept. of ComputingThe Hong Kong Polytechnic UniversityHong Kong

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