Incremental slow feature analysis with indefinite kernel for online temporal video segmentation

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 7725 LNCS, Issue PART 2, 2013, Pages 162-176

  Liwicki, Stephan ^a   Zafeiriou, Stefanos ^a   Pantic, Maja ^a,b  

^a IMPERIAL COLLEGE LONDON   (United Kingdom)

^b UNIVERSITY OF TWENTE   (Netherlands)

Author keywords

[No Author keywords available]

Indexed keywords

DATA REPRESENTATIONS; HUMAN VISUAL SYSTEM; INCREMENTAL SLOW FEATURE ANALYSIS; INDEFINITE KERNEL; QUANTITATIVE EVALUATION; SLOW FEATURE ANALYSIS(SFA); SPECIAL PROPERTIES; TEMPORAL VIDEO SEGMENTATION;

ARTIFICIAL INTELLIGENCE;

EID: 84875884940     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-37444-9_13     Document Type: Conference Paper

References (20)

1. Wiskott, L., Sejnowski, T.: Slow Feature Analysis: Unsupervised Learning of Invariances. Neural Computation 14, 715-770 (2002)
2. Nater, A., Grabner, H., Van Gool, L.: Temporal Relations in Videos for Unsupervised Activity Analysis. In: Mach. Learning, pp. 78-86 (2004)
3. Kompella, V., Luciw, M., Schmidhuber, J.: Incremental Slow Feature Analysis. In: IJCAI 2011, pp. 1354-1359 (2011)
4. Zhang, Z., Tao, D.: Slow Feature Analysis for Human Action Recognition. IEEE Trans. Pattern Anal. Mach. Intell. 34, 436-450 (2012)
5. Böhmer, W., Grünewälder, S., Nickisch, H., Obermayer, K.: Regularized sparse kernel slow feature analysis. In: Gunopulos, D., Hofmann, T., Malerba, D., Vazirgiannis, M. (eds.) ECML PKDD 2011, Part I. LNCS (LNAI), vol. 6911, pp. 235-248. Springer, Heidelberg (2011)
6. Franzius, M., Sprekeler, H., Wiskott, L.: Slowness and Sparseness Lead to Place, Head-Direction, and Spatial-View Cells. PLoS Comput. Biol. 3, 1605-1622 (2007)
7. Levy, A., Lindenbaum, M.: Sequential Karhunen-Loeve Basis Extraction and its Application to Images. IEEE Trans. Image Process. 9, 1371-1374 (2000)
8. Ross, D., Lim, J., Lin, R., Yang, M.: Incremental Learning for Robust Visual Tracking. Int. Journal of Comp. Vision 77, 125-141 (2008)
9. Weng, J., Zhang, Y., Hwang, W.: Candid Covariance-Free Incremental Principal Component Analysis. IEEE Trans. Pattern Anal. Mach. Intell. 25, 1034-1040 (2003)
10. Chin, T., Suter, D.: Incremental Kernel Principal Component Analysis. IEEE Trans. Image Process. 16, 1662-1674 (2007)
11. Zhou, F., De la Torre, F., Cohn, J.: Unsupervised Discovery of Facial Events. In: CVPR 2010, pp. 2574-2581 (2010)
12. Turaga, P., Veeraraghavan, A., Chellappa, R.: Unsupervised View and Rate Invariant Clustering of Videosequences. Comp. Vision and Image Understanding 113, 353-371 (2009)
13. Hoai, M., Lan, Z., De la Torre, F.: Joint Segmentation and Classification of Human Actions in Video. In: CVPR 2011, pp. 3265-3272 (2011)
14. Liwicki, S., Zafeiriou, S., Tzimiropoulos, G., Pantic, M.: Efficient Online Subspace Learning with an Indefinite Kernel for Visual Tracking and Recognition. IEEE Trans. Neu. Net. Learn. Systems 23, 1624-1636 (2012)
15. Tzimiropoulos, G., Argyriou, V., Zafeiriou, S., Stathaki, T.: Robust FFT-Based Scale-Invariant Image Registration with Image Gradients. IEEE Trans. Pattern Anal. Mach. Intell. 32, 1899-1906 (2010)
16. Turk, M., Pentland, A.: Eigenfaces for Recognition. Journal of Cognitive Neuroscience 3, 71-86 (1991)
17. Pȩkalska, E., Haasdonk, B.: Kernel Discriminant Analysis for Positive Definite and Indefinite Kernels. IEEE Trans. Pattern Anal. Mach. Intell. 31, 1017-1032 (2009)
18. Hassibi, B., Sayed, A., Kailath, T.: Linear Estimation in Krein Spaces. I. Theory. IEEE Trans. Automatic Control 41, 18-33 (1996)
19. Valstar, M., Pantic, M.: Induced Disgust, Happiness and Surprise: an Addition to the MMI Facial Expression Database. In: LREC 2010, pp. 65-70 (2010)
20. Fathi, A., Mori, G.: Action Recognition by Learning Mid-level Motion Features. In: CVPR 2008 (2008)