Authors:
Marion Morel
1
;
Richard Kulpa
2
;
Anthony Sorel
2
;
Catherine Achard
1
and
Séverine Dubuisson
1
Affiliations:
1
UPMC Sorbonne Universités, France
;
2
M2S Lab - University Rennes 2, France
Keyword(s):
Dynamic Time Warping, Evaluation, Multidimensional Features, Synchrony, Motion Capture.
Related
Ontology
Subjects/Areas/Topics:
Applications
;
Computer Vision, Visualization and Computer Graphics
;
Features Extraction
;
Geometry and Modeling
;
Image and Video Analysis
;
Image-Based Modeling
;
Pattern Recognition
;
Software Engineering
Abstract:
Automatically evaluating and quantifying the performance of a player is a complex task since the important motion features to analyze depend on the type of performed action. But above all, this complexity is due to the variability of morphologies and styles of both the experts who perform the reference motions and the novices. Only based on a database of experts' motions and no additional knowledge, we propose an innovative 2-level DTW (Dynamic Time Warping) approach to temporally and spatially align the motions and extract the imperfections of the novice's performance for each joints. In this study, we applied our method on tennis serve but since it is automatic and morphology-independent, it can be applied to any individual motor performance.