Visual and efficient three-dimensional human body movement data retrieval method based on demonstrated performance

Abstract

The invention discloses an intuitive and efficient three-dimensional human motion data retrieval method based on demonstration performance. The method comprises the following steps: first, to constitute a motion index for a large-capacity motion database through subspace partition; second, to set an overall reference coordinate system of a motion sensor; third, to load a standard three-dimensional human skeleton; fourth, to designate the corresponding relationship between the motion sensor and the standard three-dimensional human skeleton nodes; fifth, to bind the motion sensor and the standard three-dimensional human skeleton through posture alignment; sixth, to drive the standard three-dimensional human skeleton through the data acquired by the motion sensor to get demonstration performance motion; seventh, to make feature extraction to the demonstration performance motion through subspace partition; eighth, to load the motion index and carry out qualitative retrieval; ninth, to set parameters, and then to carry out quantitative retrieval based on the qualitative retrieval. The invention solves the problem of how to intuitively and accurately express the creation intention of animation producers in the process of making character animation to achieve rapid and efficient extraction of required motion data.

Description

technical field [0001] The invention relates to a retrieval method for three-dimensional human motion data, in particular to an intuitive and efficient three-dimensional human motion data retrieval method based on demonstration performances. Background technique [0002] According to the different input information, there are four main methods of motion retrieval: text, notation language, hand-drawn sketches, and motion samples. Traditional text retrieval methods use keyword descriptions as input (such as "first punch and then kick") to search for motion clips with these label attributes, but the content of the text description is vague, incomplete, and there are problems of inconsistent subjective understanding. Not suitable for searching large-capacity sports databases. The notation language focuses on the description of the underlying position and direction of each joint point, and can clearly express the content and meaning of the motion data [1]. However, this method r...

AI Technical Summary

Problems solved by technology

The disadvantage of this method is that the user may not have a suitable sample as input

This method solves the problem that animators are difficult to describe, not intuitive enough, and have low retrieval efficiency when inputting information when using massive motion databases for motion retrieval.

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