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Content Provider | IEEE Xplore Digital Library |
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Author | Burns, J.B. |
Copyright Year | 1996 |
Description | Author affiliation: Teleos Res., Mountain View, CA, USA (Burns, J.B.) |
Abstract | This study combines two useful methods in recognition: consensus or voting-based approaches and moment-based representations. Matches between image patches are generated using a Gaussian-weighted moment encoding of the patches and a feature indexing process. Each match implies an object 3D position and orientation (pose) and generates a vote for this pose. Recognition is accomplished by detecting significant clusters of votes in pose space. This combined method is an improvement over voting and moment methods in isolation. Using image brightness moments, the idea is demonstrated on examples of human faces undergoing full 3D pose change, as well as changes in features such as talking and blinking. The idea is then extended to moments of local texture orientation and successfully demonstrated under large variations in lighting nature and geometry. |
Starting Page | 891 |
Ending Page | 898 |
File Size | 1615915 |
Page Count | 8 |
File Format | |
ISBN | 0818672595 |
ISSN | 10636919 |
DOI | 10.1109/CVPR.1996.517177 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 1998-06-18 |
Publisher Place | USA |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Brightness Voting Image generation Gaussian processes Image coding Indexing Moment methods Humans Face detection Geometry |
Content Type | Text |
Resource Type | Article |
Subject | Computer Vision and Pattern Recognition Software |
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