Abstract
In this article, we present a method of analysis for 3D scanning sequences of human bodies in motion that allows us to obtain a computer animation of a virtual character containing both skeleton motion and high-detail deformations of the body surface geometry, resulting from muscle activity, the dynamics of the motion, and tissue inertia. The developed algorithm operates on a sequence of 3D scans with high spatial and temporal resolution. The presented method can be applied to scans in the form of both triangle meshes and 3D point clouds. One of the contributions of this work is the use of the Iterative Closest Point algorithm with motion constraints for pose tracking, which has been problematic so far. We also introduce shape maps as a tool to represent local body segment deformations. An important feature of our method is the possibility to change the topology and resolution of the output mesh and the topology of the animation skeleton in individual sequences, without requiring time-consuming retraining of the model. Compared to the state-of-the-art Skinned Multi-Person Linear (SMPL) method, the proposed algorithm yields almost twofold better accuracy in shape mapping.
Highlights
Measurement and modeling of human body movement is a research field with many visual, medical, and monitoring applications
In order to compare the results of our method with a state-of-the-art reference method, we carried out the analogous procedure for the reconstructed meshes shared by the authors of the Skinned Multi-Person Linear (SMPL) model method
In this paper, we have presented a method of analysis for human body 3D scan sequences that allows for the generation of skeletal animations, along with body shape deformation animations
Summary
Measurement and modeling of human body movement is a research field with many visual, medical, and monitoring applications. With the emergence of cheap RGBD sensors, there has been growing interest among scientists in the analysis of unidirectional 3D scans [1,2]. With the emergence of public scanning datasets, the topic of high-resolution reconstruction of motion and deformation of the human body has gained popularity. Reconstructing the movement and shape of a body on the basis of a sequence of 3D scans is a challenging task, due to the deformations of body shape deviating from rigid body dynamics and due to the amount and nature of the input data.
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