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Object Detection by Global Contour Shape

K. Schindler and D. Suter
Pattern Recognition
Vol. 41, No. 12, pp. 3736-3748, 2008


We present a method for object class detection in images based on global shape. A distance measure for elastic shape matching is derived, which is invariant to scale and rotation, and robust against non-parametric deformations. Starting from an over-segmentation of the image, the space of potential object boundaries is explored to find boundaries, which have high similarity with the shape template of the object class to be detected. An extensive experimental evaluation is presented. The approach achieves a remarkable detection rate of 83%-91% at 0.2 false positives per image on three challenging data sets.

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  author = {K. Schindler and D. Suter},
  title = {Object Detection by Global Contour Shape},
  journal = {Pattern Recognition},
  year = {2008},
  month = {},
  pages = {3736-3748},
  volume = {41},
  number = {12},
  keywords = {}