Hand Pose Estimation

(Hand Engine)

Members:   XU Chi ,   Ashwin Nanjappa ,   Zhang Xiaowei ,   Cheng Li (Project Leader)

Machine Learning For Bioimage Analysis Group

  • Introduction



We tackle the practical problem of hand pose estimation from a single noisy depth image. A dedicated three-step pipeline is proposed. We analyze the depth noises, and suggest tips to minimize their negative impacts on the overall performance. Our approach is able to work with Kinect-type noisy depth images, and reliably produces pose estimations of motions efficiently.

  • Videos

• Estimate Hand Poses Efficiently from Single Depth Images (DHand))

Annotated Hand-Depth Image Dataset and its Performance Evaluation:
http://hpes.bii.a-star.edu.sg/
  • Related Links

Lie-X: Depth Image Based Articulated Object Pose Estimation, Tracking, and Action Recognition on Lie Groups

  • Publications

[1] Chi Xu, Li Cheng. Efficient hand pose estimation from a single depth image. In International Conference on Computer Vision (ICCV), 2013. [ bib ]  [ pdf ]
[2] Chi Xu, Ashwin Nanjappa, Xiaowei Zhang, Li Cheng. Estimate Hand Poses Efficiently from Single Depth Images. In In International Journal of Computer Vision (IJCV), 2015. [ bib ]  [ pdf ]