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Multimedia Tools and Applications

, Volume 75, Issue 3, pp 1667–1699 | Cite as

Point-based medialness for 2D shape description and identification

  • Prashant AparajeyaEmail author
  • Frederic Fol Leymarie
Article

Abstract

We propose a perception-based medial point description of a natural form (2D: static or in articulated movement) as a framework for a shape representation which can then be efficiently used in biological species identification and matching tasks. Medialness is defined by adapting and refining a definition first proposed in the cognitive science literature when studying the visual attention of human subjects presented with articulated biological 2D forms in movement, such as horses, dogs and humans (walking, running). In particular, special loci of high medialness for the interior of a form in movement, referred to as “hot spots”, prove most attractive to the human perceptual system. We propose an algorithmic process to identify such hot spots. In this article we distinguish exterior from interior shape representation. We further augment hot spots with extremities of medialness ridges identifying significant concavities (from outside) and convexities (from inside). Our representation is strongly footed in results from cognitive psychology, but also inspired by know-how in art and animation, and the algorithmic part is influenced by techniques from more traditional computer vision. A robust shape matching algorithm is designed that finds the most relevant targets from a database of templates by comparing feature points in a scale, rotation and translation invariant way. The performance of our method has been tested on several databases. The robustness of the algorithm is further tested by perturbing the data-set at different levels.

Keywords

2D shape analysis Dominant points Information retrieval Medialness representation Shape compression Planar articulated movement 

Notes

Acknowledgments

This work was partially funded by the European Union (FP7 – ICT; Grant Agreement #258749; CEEDs project). Thanks to Prof. Stefan Rueger and Prof. Ilona Kovacs for useful discussions.

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Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  1. 1.Deparment of Computing, GoldsmithsUniversity of LondonLondonUK

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