Segmentation of 3D range images using pyramidal data structures
CVGIP: Image Understanding
Object Pose Detection in Range Scan Data
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Conditional models for contextual human motion recognition
Computer Vision and Image Understanding - Special issue on modeling people: Vision-based understanding of a person's shape, appearance, movement, and behaviour
MixIn3D: 3D Mixed Reality with ToF-Camera
Dyn3D '09 Proceedings of the DAGM 2009 Workshop on Dynamic 3D Imaging
SLAM combining ToF and high-resolution cameras
WACV '11 Proceedings of the 2011 IEEE Workshop on Applications of Computer Vision (WACV)
Markerless motion capture of interacting characters using multi-view image segmentation
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
FAAST: The Flexible Action and Articulated Skeleton Toolkit
VR '11 Proceedings of the 2011 IEEE Virtual Reality Conference
Geometrically consistent elastic matching of 3D shapes: A linear programming solution
ICCV '11 Proceedings of the 2011 International Conference on Computer Vision
User identification and object recognition in clutter scenes based on RGB-depth analysis
AMDO'12 Proceedings of the 7th international conference on Articulated Motion and Deformable Objects
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Pose Recovery (PR) and Human Behavior Analysis (HBA) have been a main focus of interest from the beginnings of Computer Vision and Machine Learning. PR and HBA were originally addressed by the analysis of still images and image sequences. More recent strategies consisted of Motion Capture technology (MOCAP), based on the synchronization of multiple cameras in controlled environments; and the analysis of depth maps from Time-of-Flight (ToF) technology, based on range image recording from distance sensor measurements. Recently, with the appearance of the multi-modal RGBD information provided by the low cost Kinect$^{\textsf{TM}}$ sensor (from RGB and Depth, respectively), classical methods for PR and HBA have been redefined, and new strategies have been proposed. In this paper, the recent contributions and future trends of multi-modal RGBD data analysis for PR and HBA are reviewed and discussed.