Incremental object part detection toward object classification in a sequence of noisy range images

This paper presents an incremental object part detection algorithm using a particle filter. The method infers object parts from 3D data acquired with a range camera. The range information is quantized and enhanced by local structure to partially cope with considerable measurement noise and distortion. The augmented voxel representation allows the adaptation of known track-before-detect algorithms to infer multiple object parts in a range image sequence even when each single observation does not contain enough information to do the detection. The appropriateness of the method is successfully demonstrated by two experiments for chair legs.