Similarity retrieval of motion capture data as time-series

Jiale Wang; Yuanjun He; Haishan Tian

doi:10.1117/12.650378

2 December 2005 Similarity retrieval of motion capture data as time-series

Jiale Wang, Yuanjun He, Haishan Tian

Proceedings Volume 6045, MIPPR 2005: Geospatial Information, Data Mining, and Applications; 60450R (2005) https://doi.org/10.1117/12.650378
Event: MIPPR 2005 SAR and Multispectral Image Processing, 2005, Wuhan, China

Abstract

This paper proposes a new method for motion capture data retrieval. To measure the similarity between motions, we define two distance functions: the local distance function and the global distance function. The local distance function is to measure the similarity between stationary body poses, and it is based on the weighted position distance between joint-pairs. We take the particularity of end-effectors into account by assigning them greater weights. The global distance function is to measure the overall similarity between motions. Because motions are time-series, it is necessary to align them on time axis to make the logically corresponding events at the same time point. We use the timewarp curve to describe the corresponding relationship between frames of two motions, and use the dynamic timewarping algorithm to find out the minimum sum of the local distances between all corresponding frame-pairs. This minimum sum is namely the global distance that measures the overall similarity between motions. The experiment demonstrates the effectiveness and accuracy of this method.

Citation Download Citation

Jiale Wang, Yuanjun He, and Haishan Tian "Similarity retrieval of motion capture data as time-series", Proc. SPIE 6045, MIPPR 2005: Geospatial Information, Data Mining, and Applications, 60450R (2 December 2005); https://doi.org/10.1117/12.650378

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KEYWORDS

Motion measurement

Distance measurement

Bone

Head

Databases

Detection and tracking algorithms

3D modeling

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