Shape-based recognition of wiry objects

Owen Carmichael, Martial Hebert

Research output: Chapter in Book/Report/Conference proceedingConference contribution

18 Scopus citations

Abstract

We present an approach to the recognition of complex-shaped objects in cluttered environments based on edge cues. We first use example images of the desired object in typical backgrounds to train a classifier cascade which determines whether edge pixels in an image belong to an instance of the object or the clutter. Presented with a novel image, we use the cascade to discard clutter edge pixels. The features used for this classification are localized, sparse edge density operations. Experiments validate the effectiveness of the technique for recognition of complex objects in cluttered indoor scenes under arbitrary out-of-image-plane rotation.

Original languageEnglish (US)
Title of host publicationProceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Volume2
Publication statusPublished - 2003
Externally publishedYes
Event2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Madison, WI, United States
Duration: Jun 18 2003Jun 20 2003

Other

Other2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition
CountryUnited States
CityMadison, WI
Period6/18/036/20/03

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ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Computer Vision and Pattern Recognition
  • Software
  • Control and Systems Engineering

Cite this

Carmichael, O., & Hebert, M. (2003). Shape-based recognition of wiry objects. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Vol. 2)