Efficient multiple model recognition in cluttered 3-D scenes

被引：38

作者：

Johnson, AE ^{[1
]}

Hebert, M ^{[1
]}

机构：

[1] CALTECH, Jet Prop Lab, Pasadena, CA 91125 USA

来源：

1998 IEEE COMPUTER SOCIETY CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION, PROCEEDINGS | 1998年

关键词：

D O I：

10.1109/CVPR.1998.698676

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

We present a 3-D shape-based object recognition system for simultaneous recognition of multiple objects in scenes containing clutter and occlusion. Recognition is based on matching surfaces by matching points using the.spin-image representation. The spin-image is a data level shape descriptor that is used to match surfaces represented as surface meshes. We present a compression scheme for spin-images that results in efficient multiple object recognition which we verify, with results showing the simultaneous recognition of multiple objects from a library of 20 models. Furthermore, we demonstrate the robust performance of recognition in the presence of clutter and occlusion through analysis of recognition trials on 100 scenes.

引用

页码：671 / 677

页数：7