Random tree walk toward instantaneous 3D human pose estimation

  title={Random tree walk toward instantaneous 3D human pose estimation},
  author={Ho Yub Jung and Soochahn Lee and Yong Seok Heo and Il Dong Yun},
  journal={2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
The availability of accurate depth cameras have made real-time human pose estimation possible; however, there are still demands for faster algorithms on low power processors. This paper introduces 1000 frames per second pose estimation method on a single core CPU. A large computation gain is achieved by random walk sub-sampling. Instead of training trees for pixel-wise classification, a regression tree is trained to estimate the probability distribution to the direction toward the particular… CONTINUE READING
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Ro­ bust and accurate shape model fitting using random forest regression voting

  • T. F. Cootes, M. C. Ionita, C. Lindner, P. Sauer
  • Vision-ECCV
  • 2012

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