Region-Based Feature Interpretation for Recognizing 3D Models in 2D Images
dc.date.accessioned | 2004-10-20T20:23:24Z | |
dc.date.accessioned | 2018-11-24T10:22:49Z | |
dc.date.available | 2004-10-20T20:23:24Z | |
dc.date.available | 2018-11-24T10:22:49Z | |
dc.date.issued | 1991-06-01 | en_US |
dc.identifier.uri | http://hdl.handle.net/1721.1/7039 | |
dc.identifier.uri | http://repository.aust.edu.ng/xmlui/handle/1721.1/7039 | |
dc.description.abstract | In model-based vision, there are a huge number of possible ways to match model features to image features. In addition to model shape constraints, there are important match-independent constraints that can efficiently reduce the search without the combinatorics of matching. I demonstrate two specific modules in the context of a complete recognition system, Reggie. The first is a region-based grouping mechanism to find groups of image features that are likely to come from a single object. The second is an interpretive matching scheme to make explicit hypotheses about occlusion and instabilities in the image features. | en_US |
dc.format.extent | 22413823 bytes | |
dc.format.extent | 8247283 bytes | |
dc.language.iso | en_US | |
dc.title | Region-Based Feature Interpretation for Recognizing 3D Models in 2D Images | en_US |
Files in this item
Files | Size | Format | View |
---|---|---|---|
AITR-1307.pdf | 8.247Mb | application/pdf | View/ |
AITR-1307.ps | 22.41Mb | application/postscript | View/ |