Motion capture data recovery using skeleton constrained singular value thresholding

Verfasser / Beitragende:
[Cheen-Hau Tan, JunHui Hou, Lap-Pui Chau]
Ort, Verlag, Jahr:
2015
Enthalten in:
The Visual Computer, 31/11(2015-11-01), 1521-1532
Format:
Artikel (online)
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024 7 0 |a 10.1007/s00371-014-1031-5  |2 doi 
035 |a (NATIONALLICENCE)springer-10.1007/s00371-014-1031-5 
245 0 0 |a Motion capture data recovery using skeleton constrained singular value thresholding  |h [Elektronische Daten]  |c [Cheen-Hau Tan, JunHui Hou, Lap-Pui Chau] 
520 3 |a Motion capture data could be missing due to imperfections during the acquisition process. Singular value thresholding (SVT) is an effective method to recover missing motion capture data. However, its effectiveness decreases significantly when markers are missing for longer periods of time. To alleviate this problem, we utilize the fact that human bones are rigid to constrain inter-marker distances of specific sets of markers. We extend the SVT method for mocap recovery to include skeleton constraints. On average, our proposed method improves on the SVT method by 40%, and performs 4% better than a recent state-of-the-art method at up to 11 times faster computation time. 
540 |a Springer-Verlag Berlin Heidelberg, 2014 
690 7 |a Motion capture  |2 nationallicence 
690 7 |a Mocap recovery  |2 nationallicence 
690 7 |a Matrix completion  |2 nationallicence 
700 1 |a Tan  |D Cheen-Hau  |u School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, Singapore  |4 aut 
700 1 |a Hou  |D JunHui  |u School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, Singapore  |4 aut 
700 1 |a Chau  |D Lap-Pui  |u School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, Singapore  |4 aut 
773 0 |t The Visual Computer  |d Springer Berlin Heidelberg  |g 31/11(2015-11-01), 1521-1532  |x 0178-2789  |q 31:11<1521  |1 2015  |2 31  |o 371 
856 4 0 |u https://doi.org/10.1007/s00371-014-1031-5  |q text/html  |z Onlinezugriff via DOI 
898 |a BK010053  |b XK010053  |c XK010000 
900 7 |a Metadata rights reserved  |b Springer special CC-BY-NC licence  |2 nationallicence 
908 |D 1  |a research-article  |2 jats 
949 |B NATIONALLICENCE  |F NATIONALLICENCE  |b NL-springer 
950 |B NATIONALLICENCE  |P 856  |E 40  |u https://doi.org/10.1007/s00371-014-1031-5  |q text/html  |z Onlinezugriff via DOI 
950 |B NATIONALLICENCE  |P 700  |E 1-  |a Tan  |D Cheen-Hau  |u School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, Singapore  |4 aut 
950 |B NATIONALLICENCE  |P 700  |E 1-  |a Hou  |D JunHui  |u School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, Singapore  |4 aut 
950 |B NATIONALLICENCE  |P 700  |E 1-  |a Chau  |D Lap-Pui  |u School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, Singapore  |4 aut 
950 |B NATIONALLICENCE  |P 773  |E 0-  |t The Visual Computer  |d Springer Berlin Heidelberg  |g 31/11(2015-11-01), 1521-1532  |x 0178-2789  |q 31:11<1521  |1 2015  |2 31  |o 371