Image Flow Segmentation and Estimation by Constraint Line Clustering
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Method for Registration of 3-D Shapes
IEEE Transactions on Pattern Analysis and Machine Intelligence - Special issue on interpretation of 3-D scenes—part II
Robot Vision
Estimation of 3D Motion from Stereo Images " Differential and Discrete Formulations
ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 1 - Volume 1
Tracking of the Articulated Upper Body on Multi-View Stereo Image Sequences
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
A survey of advances in vision-based human motion capture and analysis
Computer Vision and Image Understanding - Special issue on modeling people: Vision-based understanding of a person's shape, appearance, movement, and behaviour
Tracking of Human Body Parts using the Multiocular Contracting Curve Density Algorithm
3DIM '07 Proceedings of the Sixth International Conference on 3-D Digital Imaging and Modeling
6D-vision: fusion of stereo and motion for robust environment perception
PR'05 Proceedings of the 27th DAGM conference on Pattern Recognition
A system for marker-less human motion estimation
PR'05 Proceedings of the 27th DAGM conference on Pattern Recognition
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In this contribution we describe a vision system for model-based 3D detection and spatio-temporal pose estimation of objects in cluttered scenes. As low-level features, our approach requires 3D depth points along with information about their motion and the direction of the local intensity gradient. We extract these features by spacetime stereo based on local image intensity modelling. After applying a graph-based clustering approach to obtain an initial separation between the background and the object, a 3D model is adapted to the 3D point cloud based on an ICP-like optimisation technique, yielding the translational, rotational, and internal degrees of freedom of the object. We introduce an extended constraint line approach which allows to estimate the temporal derivatives of the translational and rotational pose parameters directly from the spacetime stereo data. Our system is evaluated in the scenario of person-independent "tracking by detection" of the hand-forearm limb moving in a non-uniform manner through a cluttered scene. The temporal derivatives of the current pose parameters are used for initialisation in the subsequent image. Typical accuracies of the estimation of pose differences between subsequent images are 1-3 mm for the translational motion, which is comparable to the pixel resolution, and 1-3 degrees for the rotational motion.