Generation of human depth images with body part labels for complex human pose recognition

作者：

Highlights：

• An efficient generation of large-scale dataset of human depth images with body part labels is proposed.

• The method adopts computer modeling and computer graphics techniques.

• The generated dataset can be used for training fully convolutional networks.

• The trained network can recognize human body parts in depth image.

摘要

•An efficient generation of large-scale dataset of human depth images with body part labels is proposed.•The method adopts computer modeling and computer graphics techniques.•The generated dataset can be used for training fully convolutional networks.•The trained network can recognize human body parts in depth image.

论文关键词：Human depth image,Human pose estimation,Convolutional neural network,Care robot

论文评审过程：Received 14 December 2016, Revised 30 April 2017, Accepted 1 June 2017, Available online 3 June 2017, Version of Record 12 July 2017.

论文官网地址：https://doi.org/10.1016/j.patcog.2017.06.006