Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/64827
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dc.contributor.authorWang, Dian
dc.date.accessioned2015-06-04T08:31:00Z
dc.date.available2015-06-04T08:31:00Z
dc.date.copyright2014en_US
dc.date.issued2014
dc.identifier.urihttp://hdl.handle.net/10356/64827
dc.description.abstractMotion 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.en_US
dc.format.extent79 p.en_US
dc.language.isoenen_US
dc.subjectDRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Signal processingen_US
dc.titleHuman motion capture data compressionen_US
dc.typeThesis
dc.contributor.supervisorChau Lap Puien_US
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen_US
dc.description.degreeMaster of Science (Signal Processing)en_US
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