What is this?


Estimate hand pose in 2d. Please refer to original paper.

In order to use this feature, you need to install pytorch (pytorch >= 1.4.0 is recommended).

Subscribing Topic

  • ~input (sensor_msgs/Image)

    Input image.

Publishing Topic

  • ~output/pose (jsk_recognition_msgs/HandPoseArray)

    Detected hand keypoints 2D positions and scores in image.

  • ~output/vis (sensor_msgs/Image)

    Visualization image of detected hand poses.


  • ~gpu (Int, Default: -1)

    GPU id. -1 represents CPU mode.

  • ~thre1 (Float, Default: 0.3)

    Threshold of hand bounding box heatmap value.

  • ~thre2 (Float, Default: 0.2)

    Threshold of hand keypoint heatmap value.

  • ~thre3 (Int, Default: 5)

    Threshold of undetected keypoints quantity.

  • ~visualize (Bool, Default: True)

    If ~visualize is true, draw estimated hand keypoints.

  • ~model_file (String, Required)

    Trained SRHandNet model file.


roslaunch jsk_perception sample_hand_pose_estimation_2d.launch gpu:=0


  doi = {10.1109/TIP.2019.2955280},
  title = {SRHandNet: Real-time 2D Hand Pose Estimation with Simultaneous Region Localization},
  journal = {IEEE Transactions on Image Processing},
  author = {Yangang Wang, Baowen Zhang and Cong Peng},
  number = 1,
  month = Oct.,
  volume = 29,
  year = 2019,
  pages = {2977 - 2986},
  url = {http://yangangwang.com/papers/WANG-SRH-2019-07.html},