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ECCV
2004
Springer

Recognizing Objects in Range Data Using Regional Point Descriptors

15 years 11 months ago
Recognizing Objects in Range Data Using Regional Point Descriptors
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.
Andrea Frome, Daniel Huber, Ravi Kolluri, Thomas B
Added 15 Oct 2009
Updated 15 Oct 2009
Type Conference
Year 2004
Where ECCV
Authors Andrea Frome, Daniel Huber, Ravi Kolluri, Thomas Bülow, Jitendra Malik
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