Semantic parametric body shape estimation from noisy depth sequences

By A. Ichim, Federico Tombari. 2016

8 citations recorded by the source corpus.

Subfields: Computational Mechanics, Computer Vision and Pattern Recognition

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computational Mechanics

1. William A. Hoff
2. Brian Reily
3. Fei Han
4. Hao Zhang

In Computer Vision and Pattern Recognition

1. Fei Han
2. William A. Hoff
3. Brian Reily
4. Hao Zhang
5. Jun Liu
6. G. Wang
7. Alex ChiChung Kot
8. Ling-yu Duan

Citations in the corpus

• Space-Time Representation of People Based on 3D Skeletal Data: A Review (2016, methodology): “ime [71] 3D non-rigid matching based on MRF deformation model Depth image sequence 3D skeleton [72] Geodesic distance & optical flow RGBD image streams 3D skeleton, 16 joints, robust to occlusions [73] energy cost optimization with multi-constraints Depth image sequence model per frame = 3ms [74]”