Stacked denoising autoencoder for feature representation learning in pose-based action recognition

2014 IEEE 3rd Global Conference on Consumer Electronics, GCCE 2014

Volumn , Issue , 2014, Pages 684-688

  Budiman, Arif ^a   Fanany, Mohamad Ivan ^a   Basaruddin, Chan ^a  

^a UNIVERSITY OF INDONESIA   (Indonesia)

Author keywords

[No Author keywords available]

Indexed keywords

CONSUMER ELECTRONICS; LEARNING SYSTEMS;

ACTION RECOGNITION; AUTO ENCODERS; BODY LANGUAGE; FEATURE REPRESENTATION; HUMAN POSE; ITERATIVE LEARNING; PUBLIC DATASET; SUPERVISED CLASSIFIERS;

MOTION ESTIMATION;

EID: 84946686986     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/GCCE.2014.7031302     Document Type: Conference Paper

References (17)

1. G. F. Angela Yao, Juergen Gall and L. V. Gool, Does human action recognition benefit from pose estimation? in Proceedings of the British Machine Vision Conference. BMVA Press, 2011, pp. 67.1-67.11
2. A. Budiman and M. Fanany, Pose-based 3d human motion analysis using extreme learning machine, in Consumer Electronics (GCCE), 2013 IEEE 2nd Global Conference on, Oct 2013, pp. 3-7
3. M. Raptis, D. Kirovski, and H. Hoppe, Real-time classification of Dance gestures from skeleton animation, in Proceedings of the 2011 ACM SIGGRAPH/Eurographics Symposium on Computer Animation, ser. SCA 11, 2011, pp. 147-156
4. A. K. Jain, Data clustering: 50 years beyond k-means, Pattern Recogn. Lett., vol. 31, no. 8, pp. 651-666, Jun. 2010
5. X. Wu, V. Kumar, J. Ross Quinlan, J. Ghosh, Q. Yang, H. MotoDa, G. J. McLachlan, A. Ng, B. Liu, P. S. Yu, Z.-H. Zhou, M. Steinbach, D. J. Hand, and D. Steinberg, Top 10 algorithms in Data mining, Knowl. Inf. Syst., vol. 14, no. 1, pp. 1-37, Dec. 2007
6. Y. Bengio, Learning deep architectures for ai, Found. Trends Mach. Learn., vol. 2, no. 1, pp. 1-127, Jan. 2009
7. Y. Bengio and Y. LeCun, Scaling learning algorithms towards ai, in Large-Scale Kernel Machines, L. Bottou, O. Chapelle, D. DeCoste, and J. Weston, Eds. MIT Press, 2007
8. M. Baccouche, F. Mamalet, C. Wolf, C. Garcia, and A. Baskurt, Sequential deep learning for human action recognition, in Proceedings of the Second International Conference on Human Behavior Unterstanding, ser. HBU11, 2011, pp. 29-39
9. P. Vincent, H. Larochelle, I. Lajoie, Y. Bengio, and P.-A. Manzagol, Stacked denoising autoencoDers: Learning useful representations in a deep network with a local denoising criterion, J. Mach. Learn. Res., vol. 11, pp. 3371-3408, Dec. 2010
10. A. Coates, H. Lee, and A. Ng, An analysis of single-layer networks in unsupervised feature learning, in Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics, ser. JMLR Workshop and Conference Proceedings, G. Gordon, D. Dunson, and M. Dudk, Eds. JMLR W&CP, pp. 215-223
11. S. Escalera, J. Gonzalez, X. Baro, M. Reyes, O. Lopes, I. Guyon, V. Athitsos, and H. Escalante, Multi-moDal gesture recognition challenge 2013: Dataset and results, in Proceedings of the 15th ACM on International Conference on MultimoDal Interaction, ser. ICMI 13, 2013, pp. 445-452
12. R. B. Palm, Prediction as a candiDate for learning deep hierarchical models of Data, 2012
13. M. Chen, Z. Xu, K. Weinberger, and F. Sha, Marginalized denoising autoencoDers for domain aDaptation, in Proceedings of the 29th International Conference on Machine Learning (ICML-12), ser. ICML 12, J. Langford and J. Pineau, Eds. New York, NY, USA: ACM, July 2012, pp. 767-774
14. C. Song, F. Liu, Y. Huang, L. Wang, and T. Tan, Auto-encoDer based Data clustering, in CIARP (1), 2013, pp. 117-124
15. A robust online sequential extreme learning machine, in AdVances in Neural Networks ISNN 2007, ser. Lecture Notes in Computer Science, D. Liu, S. Fei, Z.-G. Hou, H. Zhang, and C. Sun, Eds., 2007, vol. 4491
16. N. Neverova, C. Wolf, G. Paci, G. Sommavilla, G. W. Taylor, and F. Nebout, A multi-scale approach to gesture detection and recognition, in ICCV Workshop on UnDerstanding Human Activities: Context and Interactions (HACI 2013), Dec. 2013, pp. 484-491
17. A. Budiman, I. Fanany, and C. Basaruddin, Constructive, robust and aDaptive OS-ELM in human action recognition, in International Conference on Industrial Automation, Information and Communication Technology 2014 (IAICT 2014), Bali, Indonesia, Aug. 2014, pp. 39-45