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ECCV
2004
Springer

Recognizing Objects in Range Data Using Regional Point Descriptors

11 years 4 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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