Recognizing Objects in Range Data Using Regional Point Descriptors (2004)
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| Venue: | EUROPEAN CONFERENCE ON COMPUTER VISION |
| Citations: | 76 - 5 self |
BibTeX
@INPROCEEDINGS{Frome04recognizingobjects,
author = {Andrea Frome and Daniel Huber and Ravi Kolluri and Thomas Bülow and Jitendra Malik},
title = {Recognizing Objects in Range Data Using Regional Point Descriptors},
booktitle = {EUROPEAN CONFERENCE ON COMPUTER VISION},
year = {2004},
pages = {224--237},
publisher = {}
}
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Abstract
Recognition of three dimensional (3D) objects in noisy and cluttered scenes is a challenging problem in 3D computer vision. One approach that has been successful in past research is the regional shape descriptor. In this paper, we introduce two new regional shape descriptors: 3D shape contexts and harmonic shape contexts. We evaluate the performance of these descriptors on the task of recognizing vehicles in range scans of scenes using a database of 56 cars. We compare the two novel descriptors to an existing descriptor, the spin image, showing that the shape context based descriptors have a higher recognition rate on noisy scenes and that 3D shape contexts outperform the others on cluttered scenes.
