International Journal of Computer Vision vol:83 issue:1 pages:72-84
This article presents a novel approach to markerless real-time pose recognition in a multicamera setup. Body pose is retrieved using example-based classification based on Haar wavelet-like features to allow for real-time pose recognition. Average Neighborhood Margin Maximization (ANMM) is introduced as a powerful new technique to train Haar-like features. The rotation invariant approach is implemented for both 2D classification based on silhouettes, and 3D classification based on visual hulls.
Van den Bergh M., Koller-Meier E., Van Gool L., ''Real-time body pose recognition using 2D or 3D haarlets'', International journal of computer vision, vol. 83, no. 1, pp. 72-84, June 2009.