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Human motion capture data compression

Authors: Wang, Dian;

Human motion capture data compression

Abstract

Motion capture is becoming more and more important in current society and has been used in many sectors of industry, agriculture, transport, education, health and sports, especially in the medicine industry, sports science, sports coaching, modern animation and video game production and other fields. Three main categories of motion capture systems in modern society are optical systems, magnetic systems and mechanical systems. This project uses two kinds of motion capture data as experiment materials, namely, data from Kinect and data from CMU database. The dissertation contains the study of kinematics related to the data format of motion capture, the filtering technology to pre-process and post-process the motion capture data, and the various compression technology to do the motion data processing experiments. According to the compression result, SNR and MAE performance has been discussed to estimate the methods. The result is analyzed horizontally and vertically while seen horizontally, the performance comparison are conducted between data from Kinect and data from database and seen vertically, the performance comparison are conducted between different types of motions, such as walk, jump, dance and run. In the same time, some important parameters are estimated according to the effect on the exercise performance.

Master of Science (Signal Processing)

Country
Singapore
Related Organizations
Keywords

DRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Signal processing

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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