Incremental Object Part Detection toward Object Classification in a Sequence of Noisy Range Images
Stefan Gächter, Ahad Harati, Roland Siegwart · Repository for Publications and Research Data (ETH Zurich) · 2008
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 uniquely quantized and enhanced by local structure information 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.The appropriateness of the method is successfully demonstrated by an experiment.