TY - GEN
T1 - The online gait measurement for characteristic gait animation synthesis
AU - Makihara, Yasushi
AU - Okumura, Mayu
AU - Yagi, Yasushi
AU - Morishima, Shigeo
N1 - Funding Information:
Acknowledgement. This work is supported by the Special Coordination Funds for Promoting Science and Technology of Ministry of Education, Culture, Sports, Science and Technology.
Publisher Copyright:
© Springer-Verlag Berlin Heidelberg 2011.
PY - 2011
Y1 - 2011
N2 - This paper presents a method to measure online the gait features from the gait silhouette images and to synthesize characteristic gait animation for an audience-participant digital entertainment. First, both static and dynamic gait features are extracted from the silhouette images captured by an online gait measurement system. Then, key motion data for various gaits are captured and a new motion data is synthesized by blending key motion data. Finally, blend ratios of the key motion data are estimated to minimize gait feature errors between the blended model and the online measurement. In experiments, the effectiveness of gait feature extraction were confirmed by using 100 subjects from OU-ISIR Gait Database and characteristic gait animations were created based on the measured gait features.
AB - This paper presents a method to measure online the gait features from the gait silhouette images and to synthesize characteristic gait animation for an audience-participant digital entertainment. First, both static and dynamic gait features are extracted from the silhouette images captured by an online gait measurement system. Then, key motion data for various gaits are captured and a new motion data is synthesized by blending key motion data. Finally, blend ratios of the key motion data are estimated to minimize gait feature errors between the blended model and the online measurement. In experiments, the effectiveness of gait feature extraction were confirmed by using 100 subjects from OU-ISIR Gait Database and characteristic gait animations were created based on the measured gait features.
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U2 - 10.1007/978-3-642-22021-0_36
DO - 10.1007/978-3-642-22021-0_36
M3 - Conference contribution
AN - SCOPUS:79960434973
SN - 9783642220203
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 325
EP - 334
BT - Virtual and Mixed Reality - New Trends - International Conference, Virtual and Mixed Reality 2011, Held as Part of HCI International 2011, Proceedings
A2 - Shumaker, Randall
PB - Springer Verlag
T2 - 4th International Conference on Virtual and Mixed Reality, Virtual and Mixed Reality 2011, held as part of the 14th International Conference on Human-Computer Interaction, HCI International 2011
Y2 - 9 July 2011 through 14 July 2011
ER -