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WACV
2005
IEEE

3D Recognition and Segmentation of Objects in Cluttered Scenes

8 years 12 months ago
3D Recognition and Segmentation of Objects in Cluttered Scenes
In this paper we present a novel view point independent range image segmentation and recognition approach. We generate a library of 3D models off-line and represent each model with our tensor-based representation. Tensors represent local surface patches of the models and are indexed by a 4D hash table. During the online phase, a seed point is randomly selected from the range image and its neighbouring surface is represented with a tensor. This tensor is simultaneously matched with all the tensors of the library models using a voting scheme. The model which receives the most votes is hypothesized to be present in the scene. The model from the library is then transformed to the range image coordinates. If the model aligns accurately with a portion of the range image, that portion is recognized, segmented and removed. Another seed point is picked from the remaining range image and the matching process is repeated until the entire scene is segmented or no further library objects can be re...
Ajmal S. Mian, Mohammed Bennamoun, Robyn A. Owens
Added 25 Jun 2010
Updated 25 Jun 2010
Type Conference
Year 2005
Where WACV
Authors Ajmal S. Mian, Mohammed Bennamoun, Robyn A. Owens
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