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Towards Multi-View Object Class Detection

A. Thomas, V. Ferrari, B. Leibe, T. Tuytelaars, B. Schiele, and L. Van Gool
IEEE Conference on Computer Vision and Pattern Recognition (CVPR'06)
New York, USA, June 2006

Abstract

We present a novel system for generic object class detection. In contrast to most existing systems which focus on a single viewpoint or aspect, our approach can detect object instances from arbitrary viewpoints. This is achieved by combining the Implicit Shape Model for object class detection proposed by Leibe and Schiele with the multi-view specific object recognition system of Ferrari {\em et al.} After learning single-view codebooks, these are interconnected by so-called activation links, obtained through multi-view region tracks across different training views of individual object instances. During recognition, these integrated codebooks work together to determine the location and pose of the object. Experimental results demonstrate the viability of the approach and compare it to a bank of independent single-view detectors.


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@InProceedings{eth_biwi_00400,
  author = {A. Thomas and V. Ferrari and B. Leibe and T. Tuytelaars and B. Schiele and and L. Van Gool},
  title = {Towards Multi-View Object Class Detection},
  booktitle = {IEEE Conference on Computer Vision and Pattern Recognition (CVPR'06)},
  year = {2006},
  month = {June},
  keywords = {}
}