Referenced Items are not available for this document.
Much of the recent research in object recognition has adopted an appearance-based scheme, wherein objects to be recognized are represented as a collection of prototypes in a multidimensional space spanned by a number of characteristic vectors (eigen-images) obtained from training views. In this paper, we extend the appearance-based recognition scheme to handle range (shape) data. The result of training is a set of `eigensurfaces' that capture the gross shape of the objects. These techniques are used to form a system that recognizes objects under an arbitrary rotational pose transformation. The system has been tested on a 20 object database including free-form objects and a 54 object database of manufactured parts. Experiments with the system point out advantages and also highlight challenges that must be studied in future research
Published in:
Computer Vision and Pattern Recognition, 1999. IEEE Computer Society Conference on.
(Volume:2
)
Date of Conference: 1999
- Meeting Date :
- 23 Jun 1999-25 Jun 1999
- ISSN :
- 1063-6919
- Print ISBN:
- 0-7695-0149-4
- INSPEC Accession Number:
- 6338800
- Conference Location :
- Fort Collins, CO
- Digital Object Identifier :
- 10.1109/CVPR.1999.784728
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