Tactile sequence classification using joint kernel sparse coding

Proceedings of the International Joint Conference on Neural Networks

Volumn 2015-September, Issue , 2015, Pages

  Yang, Jingwei ^a,b   Liu, Huaping ^b   Sun, Fuchun ^b   Gao, Meng ^a  

^a SHIJIAZHUANG TIEDAO UNIVERSITY   (China)

^b TSINGHUA UNIVERSITY   (China)

Author keywords

joint sparse coding; kernel sparse coding; tactile sequence classification

Indexed keywords

CLASSIFICATION (OF INFORMATION); INTELLIGENT ROBOTS;

INTRINSIC RELATION; MULTI FINGERS; MULTIPLE OBJECTS; ROBOTIC FINGERTIP; SEQUENCE CLASSIFICATION; SPARSE CODING; SPATIAL FEATURES; TACTILE SENSORS;

CODES (SYMBOLS);

EID: 84950970488     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IJCNN.2015.7280512     Document Type: Conference Paper

References (21)

1. Y. Bekiroglu, and J. Laaksonen, "Assessing grasp stability based on learning and haptic data," IEEE Transactions on Robotics, vol. 27, no. 3, pp. 616-629,2011.
2. Y. Bekiroglu, D. Kragic, and V. Kyrki, "Learning grasp stability based on tactile data and HMMs," Robot and Human Interactive Communication, pp. 132-137,2010.
3. Z. Chen, W. Zuo, Q. Hu, and L. Lin, "Kernel sparse representation for time series c1assificaion," information Science, voI. 292, pp. 15-26,2015.
4. A. Drimus, G. Kootstra, and A. Bilberg, "Design of a flexible tactile sensor for classification of rigid and deformable objects," Robotics and Autonomous Systems, vo1. 62, no. I, pp. 3-15, 2014.
5. C. Goldfeder, M. Ciocarlie, and H. Dang, "The Columbia grasp database," in: Proc. oJ into Con]. on Robotics and Automation (ICRA), pp. 1710-1716, 2009.
6. S. Gao, T. W. H. Tsang and L. T. Chi a, "Kernel sparse representation for image classification and face recognition," in Proc. llth Eur. Con Comput. Vis. (ECCV), vol. 63 14, pp:I-14, 2010.
7. A. Jalalian, S. K. Chalup, "GDTW-P-SVMs,wariable-length time series analysis using support vector machines," Neurocomputing, vol. 99, no. I, pp. 270-282, 2013.
8. E. Keogh, "Exact indexing of dynamic time warping," Proceedings oJ the 28th VLDB Conference, Hong Kong, China, vol. 7, no. 3, pp:358-386, 2002.
9. A. Khasnobish, A. Jati, G. Singh, S. Bhattcharyya, A. Konar, et aI, "Object-shape recognition from tactile images using a feed-forward neural network," IEEE World Congress on Computational Intelligence(WCCI), Brisbane, Australia, pp. 1-8,2012.
10. H. Liu, J. Greco, and X. Song, "Tactile image based contact shape recognition using neural network," in: Proc. oJ Multisensor Fusion and Integration Jor Intelligent Systems(MFI), pp. 138-143,2012.
11. S. Li, L. Xu, and X. Wang, "Compressed sensing signal and data acquisition in wireless sensor networks and Internet of things," iEEE Transactions on Industrial InJormatics, vol. 9, no. 4, pp. 2177-2186, 2013.
12. M. Madry, L. Bo, D. Kragic, and D. Fox, "ST-HMP: Unsupervised spatiotemporal feature learning for tactile data," in: Proc. oJ Int. Con on Robotics and Automation (lCRA), 2014.
13. H. V. Nguyen, V. M. Patel, N. M. Nasrabadi, and R. Chellappa, "Design of non-linear kernel dictionaries for object recognition," IEEE Transactions on Image Processing, vol. 22, no. 12, pp. 5123-5135,2013.
14. H. Soh, Y. Su, and Y. Demiris, "Online spatio-temporal Gaussian process experts with application to tactile classification," in: Proc. oJ 1nl. Con on intelligent Robots and Systems (IROS),Vilamoura, Algarve, Portugal, pp. 4489-4496, 2012.
15. M. Schopfer, M. Pardowitz, and R. Haschke, "Identifying relevant tactile features for object identification," Towards Service Robots Jor Everyday Environments, vol. 76, pp. 417-430, 2012.
16. J. Wright, Y. Ma, J. Mairal, G. Sapiro, T. S. Huang, and S. Van, "Sparse representation for computer vision and pattern recognition," Proceedings oJ the iEEE, vol. 98, no. 6, pp. 1031-1044,2010.
17. Wei Xiao, Fuchun Sun, Huaping Liu, and Chao He, "Dexterous RoboticHand Grasp Learning Using Piecewise Linear Dynamic Systems Model," Foundations and Practical Applications oJ Congnitive Systems and Information Processing, vol. 215, pp. 845-855,2014.
18. J. Yang, J. Wright, T. S. Huang, and Y. Ma, "Image super-resolution via sparse representation," iEEE Tranactions on Image Processing, vol. 19, no. ll, pp. 2861-2873,2010.
19. S. Yang, Y. Han, and X. Zang, "A sparse kernel representation method for image," IEEE World Congress on Computational Intelligence(WCCi), Brisbane, Australia, pp. 10-15,2012.
20. X. T. Yuan, X. Liu, S. Van, "Visual classification with multitasd joint sparse representation," IEEE Transactions on Image Processing, vol. 21, no. 10, pp. 4349-4360.
21. J. Zhang, C. Song, and Y. Hu, "Improving robustness of robotic grasping by fusing multi-sensor," in: Proc. oJ Multisensor Fusion and Integration Jor intelligent Systems(MFI), Hamburg, Germany, pp. 126-13I, 2012.