| The analysis of motion similarity, particularly human motion similarity, is needed in different areas of study: motion blending, where new motions are generated from previous ones and they are intended to be as realistic as possible; motion retrieval, where indexing, searching and retrieving a particular movement from databases of motions capture data is required; and performance analysis of dancers and athletes, where the examination of recorded dances and exercises allows to track the evolution of characteristics to be analyzed, such as strength, speed, etc.;This dissertation offers a framework for measuring human motion similarity by modeling human motion as a set of 3-dimensional curves represented as orthogonal changes of direction, and then by using a human movement notation that describes such human motion in a way that temporal and spatial analysis of human motion similarity can be achieved.;For purposes of evaluating the feasibility of this approach, a set of baseline key rehabilitation exercises has been chosen and tested using our implementation. Motion capture sessions for the key rehabilitation exercises provided the data for the experiments. FastDTW, an algorithm for measuring similarity between two temporal sequences, was used to compare the result of our implementation.;One of the main contributions of this proposal is the modeling of human motion as chain codes, or strings composed of characters from a finite alphabet. This model of human motion allows the use of string matching algorithms, sequence alignment algorithms, and statistical analysis approaches to achieve the analysis of similarity. Another contribution is the ability of spatial and temporal analysis due to the proposed model and description of the human motion. This technique takes data from a motion capture session, regardless the technique used in those sessions. The only requirement is that data must contain timed three-dimensional positions of the markers used, and information regarding the part of the body those markers were set during the motion capture session. Finally, based on the description of the key rehabilitation exercises, we suggested enhancements for LABANotation such purpose. |
