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CS 297 Deliverable 4
Human Bone Points Detection and Dataset Generation.
DESCRIPTION
This deliverable is aimed at identifying bone points of the humanoid avatar for the videos generated in Deliverable 3. Also a reseacrh paper on Skeleton based Action Recognition using CNN was studied.
The bone keypoints were detected using the OpenPose model.
About OpenPose : It is a realtime approach for single-person 3D keypoint detection : body, foot, hand, and facial keypoints.
About Skeleton based Action Recognition: This paper proposed a (CNN) based framework for both action classification and detection.
The video dataset generated here would be used to train an AI model to recognize the action performed by the humanoid avatar in a 3D space by implementing the approcach given in above paper.
PREVIEW
Input to the OpenPose Model
Output from the OpenPose Model
DOWNLOADS
Humanoid Skelton Video Dataset
Skeleton-based Action Recognition with Convolutional Neural Networks-PDF
REFERENCES
- Z. Cao, G. Hidalgo, T. Simon, S. Wei, and Y. Sheikh, "OpenPose: Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields," 2018. [Online]. Available: arXiv:1812.08008
- C. Li, Q. Zhong, D. Xie, and S. Pu, "Skeleton-based Action Recognition with Convolutional Neural Networks," 2017. [Online]. Available: arXiv:1704.07595