In short, you record a piece of video with human motions, through this project you will see a 3D model acting the same motions as what you do in the video. OpenMMD can be referred as OpenPose + MikuMikuDance (MMD).

OpenMMD represents the OpenPose-Based Deep-Learning project that can directly convert real-person videos to the motion of animation models (i.e. All the above yield a 33% accuracy improvement on the Human 3.6 Million (H3.6M) dataset compared to the baseline method (MocapNET) while maintaining real-time performance (c) An efficient Inverse Kinematics solver that refines the neural-network-based solution providing 3D human pose estimations that are consistent with the limb sizes of a target person (if known). This permits the recovery of the human pose even in the case of significant occlusions. (b) A human body orientation classifier and an ensemble of orientation-tuned neural networks that regress the 3D human pose by also allowing for the decomposition of the body to an upper and lower kinematic hierarchy. Our contributions include: (a) A novel and compact 2D pose NSRM representation. We present MocapNET, a real-time method that estimates the 3D human pose directly in the popular Bio Vision Hierarchy (BVH) format, given estimations of the 2D body joints originating from monocular color images.

Mmd how to open avi files