Research
HybridFusion: Real-time Performance Capture Using a Single Depth Sensor and Sparse IMUs
Z. Zheng, T. Yu, H. Li, K. Guo, Q. Dai, L. Fang, Y. Liu
European Conference on Computer Vision 2018 -- ECCV 2018
We propose a light-weight and highly robust real-time human performance capture method based on a single depth camera and sparse inertial measurement units (IMUs). Our system enables non-rigid surface reconstruction for fast motions and challenging poses with severe occlusions.
DoubleFusion: Real-time Capture of Human Performances with Inner Body Shapes from a Single Depth Sensor
T. Yu, Z. Zheng, K. Guo, J. Zhao, Q. Dai, H. Li, G. Pons-Moll, Y. Liu
IEEE Conference on Computer Vision and Pattern Recognition 2018 -- CVPR 2018 Oral
We propose DoubleFusion, a new real-time system that combines volumetric dynamic reconstruction with datadriven template fitting to simultaneously reconstruct detailed geometry, non-rigid motion and the inner human body shape from a single depth camera.