Capturing Upper Body Motion in Conversation-Reference-Cited by-同舟云学术

Capturing Upper Body Motion in Conversation

Published:2014-11-12 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 16th International Conference on Multimodal Interaction
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Author:

Marcos-Ramiro Alvaro¹,Pizarro-Perez Daniel²,Marron-Romera Marta¹,Gatica-Perez Daniel³

Affiliation:

1. University of Alcala, Alcala de Henares, Madrid, Spain

2. University of Clermond-Ferrand, Clermond-Ferrand, France

3. Idiap Research Institute & Ecole Polytechnique Federale de Lausanne, Martigny, Switzerland

Funder

Swiss National Science Foundation

Ministerio de Ciencia e Innovación

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/2663204.2663267

Reference35 articles.

1. Chalearn gesture dataset (cgd2011) chalearn california 2011. copyright (c) chalearn - 2011. http://gesture.chalearn.org/data. Chalearn gesture dataset (cgd2011) chalearn california 2011. copyright (c) chalearn - 2011. http://gesture.chalearn.org/data.

2. A. Agarwal and B. Triggs. Recovering 3d human pose from monocular images. IEEE PAMI 28(1) 2006. 10.1109/TPAMI.2006.21 A. Agarwal and B. Triggs. Recovering 3d human pose from monocular images. IEEE PAMI 28(1) 2006. 10.1109/TPAMI.2006.21

3. P. Buehler M. Everingham D. P. Huttenlocher and A. Zisserman. Upper body detection and tracking in extended signing sequences. IJCV 95(2) 2011. Figure 7: Qualitative results. Left: comparison with the baselines {9} and {22}. Top center: failure cases. From left to right: untrained pose not enough movement information torso detection failure. Bottom center: HumanEva I results for S1 and S3. Failure cases from left to right: untrained pose torso detection failure. Top right: speed histograms for each hand. Bottom right: examples of obtained poses in ChaLearn 2011. Best viewed in PDF in high zoom. 10.1007/s11263-011-0480-9 P. Buehler M. Everingham D. P. Huttenlocher and A. Zisserman. Upper body detection and tracking in extended signing sequences. IJCV 95(2) 2011. Figure 7: Qualitative results. Left: comparison with the baselines {9} and {22}. Top center: failure cases. From left to right: untrained pose not enough movement information torso detection failure. Bottom center: HumanEva I results for S1 and S3. Failure cases from left to right: untrained pose torso detection failure. Top right: speed histograms for each hand. Bottom right: examples of obtained poses in ChaLearn 2011. Best viewed in PDF in high zoom. 10.1007/s11263-011-0480-9

4. A First-Order Primal-Dual Algorithm for Convex Problems with Applications to Imaging