Shape-based Recognition Of Wiry Objects

Owen Carmichael and Martial Hebert
IEEE Conference On Computer Vision And Pattern Recognition, June, 2003.


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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.

Keywords
object recognition, shape, cascade, learning, clutter

Notes
Associated Center(s) / Consortia: Vision and Autonomous Systems Center
Number of pages: 8

Text Reference
Owen Carmichael and Martial Hebert, "Shape-based Recognition Of Wiry Objects," IEEE Conference On Computer Vision And Pattern Recognition, June, 2003.

BibTeX Reference
@inproceedings{Carmichael_2003_4386,
   author = "Owen Carmichael and Martial Hebert",
   title = "Shape-based Recognition Of Wiry Objects",
   booktitle = "IEEE Conference On Computer Vision And Pattern Recognition",
   publisher = "IEEE Press",
   month = "June",
   year = "2003",
}