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Multi-View Human Model Fitting Using Bone Orientation Constraint and Joints Triangulation

Citation Author(s):
Jordy Ajanohoun, Eric Paquette, Carlos Vazquez
Submitted by:
Jordy Ajanohoun
Last updated:
27 September 2021 - 1:39pm
Document Type:
Poster
Document Year:
2021
Event:
Presenters:
Jordy Ajanohoun
Paper Code:
1216
 

We address 3D human pose and shape estimations from multi-view images. We use the SMPL body model, and regress the model parameters that best fit the shape and pose. To solve for the parameters, we first compute 3D joint positions from 2D joint estimations on images by using a linear algebraic triangulation. Then, we fit the 3D parametric body model to the 3D joints while imposing a bone orientation constraint between the 3D model and the corresponding body parts detected in the images. We do so by minimizing a new set of objective functions through a two-step optimization process that provides a good initialization for the refinement of the shape and pose parameters. Our approach is evaluated on the Human3.6M and HumanEva benchmarks, showing superior results with respect to state-of-the-art methods.

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