NDLI: Using the Particle Filter Approach to Building Partial Correspondences Between Shapes

Content Provider	Springer Nature Link
Author	Lakaemper, Rolf Sobel, Marc
Copyright Year	2009
Abstract	Constructing correspondences between points characterizing one shape with those characterizing another is crucial to understanding what the two shapes have in common. These correspondences are the basis for most alignment processes and shape similarity measures. In this paper we use particle filters to establish perceptually correct correspondences between point sets characterizing shapes. Local shape feature descriptors are used to establish the probability that a point on one shape corresponds to a point on the other shape. Global correspondence structures are calculated using additional constraints on domain knowledge. Domain knowledge is characterized by prior distributions which serve to characterize hypotheses about the global relationships between shapes. These hypotheses are formulated online. This means global constraints are learnt during the particle filtering process, which makes the approach especially interesting for applications where global constraints are hard to define a priori. As an example for such a case, experiments demonstrate the performance of our approach on partial shape matching.
Starting Page	1
Ending Page	23
Page Count	23
File Format	PDF
ISSN	09205691
Journal	International Journal of Computer Vision
Volume Number	88
Issue Number	1
e-ISSN	15731405
Language	English
Publisher	Springer US
Publisher Date	2009-08-26
Publisher Place	Boston
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Shape matching Particle filters Shape recognition Feature correspondences Shape alignment Pattern Recognition Image Processing and Computer Vision Artificial Intelligence (incl. Robotics) Computer Imaging, Vision, Pattern Recognition and Graphics
Content Type	Text
Resource Type	Article
Subject	Artificial Intelligence Computer Vision and Pattern Recognition Software

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