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Conference Papers Year : 2022

On the Feasible Regions Delimiting Natural Human Postures in a Novel Skeletal Representation

Abstract

The de facto standard for storing human motion data on a computer involves a representation based on Euler angles. This representation, while effective, has several shortcomings. Triplets of Euler angles are not unique, and the same posture may be expressed using different combinations of angles. Furthermore, many possible Euler angle triplets correspond to unnatural positions for human joints. This means that, in general, a large part of the representational space remains unused. In this paper, we further investigate a recently proposed representation inspired by molecular representations. It uses only two (instead of three) degrees of freedom per joint: a vector and a torsion angle. Using the two key ingredients of this new representation, we present a complete analysis of the Graphics Lab Motion Capture Database. The data found in this analysis provide us with some powerful insights about natural and unnatural human postures in human motions. These insights can potentially lead to possible constraints on human motions which may be used to more effectively solve open problems in the computer graphics community, most notably the problem of (human) motion adaptation.
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Dates and versions

hal-03746440 , version 1 (05-08-2022)
hal-03746440 , version 2 (13-09-2022)

Identifiers

  • HAL Id : hal-03746440 , version 2

Cite

Simon Hengeveld, Antonio Mucherino. On the Feasible Regions Delimiting Natural Human Postures in a Novel Skeletal Representation. IEEE Proceedings of the 17th conference on Computer Science and Intelligence Systems, Sep 2022, Sofia, Bulgaria. ⟨hal-03746440v2⟩
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