A comparison of features in parts-based object recognition hierarchies

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

Volumn 4669 LNCS, Issue PART 2, 2007, Pages 210-219

  Hasler, Stephan ^a   Wersing, Heiko ^a   Körner, Edgar ^a  

^a HONDA RESEARCH INSTITUTE EUROPE GMBH   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

FACE RECOGNITION; FEATURE EXTRACTION; MATHEMATICAL MODELS;

CATEGORIZATION SCENARIOS; CATEGORY DISCRIMINATION; GRAY-SCALE IMAGES;

HIERARCHICAL SYSTEMS;

EID: 38149020802     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-74695-9_22     Document Type: Conference Paper

References (16)

1. Tanaka, K.: Inferotemporal Cortex And Object Vision. Annual Review of Neuroscience 19, 109-139 (1996)
2. Tsunoda, K., Yamane, Y., Nishizaki, M., Tanifuji, M.: Complex objects are represented in inferotemporal cortex by the combination of feature columns. Nature Neuroscience 4(8), 832-838 (2001)
3. Wersing, H., Körner, E.: Learning Optimized Features for Hierarchical Models of Invariant Object Recognition. Neural Computation 15(7), 1559-1588 (2003)
4. Serre, T., Wolf, L., Bileschi, S., Riesenhuber, M., Poggio, T.: Robust Object Recognition with Cortex-Like Mechanisms. IEEE Trans. Pattern Analysis and Machine Intelligence 29(3), 411-426 (2007)
5. Mel, B.W.: SEEMORE: Combining color, shape, and texture histogramming in a neurally inspired approach to visual object recognition. Neural Computation 9(4), 777-804 (1997)
6. Schiele, B., Crowley, J.L.: Object Recognition Using Multidimensional Receptive Field Histograms. In: European Conference on Computer Vision, pp. 1039-1046. Cambridge, UK (1996)
7. Turk, M., Pentland, A.: Eigenfaces for Recognition. Journal of Cognitive Neuroscience 3(1), 71-86 (1991)
8. Lee, D.D., Seung, H.S.: Learning the parts of objects by non-negative matrix factorization. Nature 401, 788-791 (1999)
9. Hasler, S., Wersing, H., Körner, E.: Class-specific Sparse Coding for Learning of Object Representations. In: Duch, W., Kacprzyk, J., Oja, E., Zadrożny, S. (eds.) ICANN 2005. LNCS, vol. 3696, pp. 475-480. Springer, Heidelberg (2005)
10. Ullman, S., Vidal-Naquet, M., Sali, E.: Visual features of intermediate complexity and their use in classification. Nature Neuroscience Vision Research 5(7), 682-687 (2002)
11. Lowe, D.C.: Distinctive Image Features from Scale-Invariant Keypoints. International Journal of Computer Vision 60(2), 91-110 (2004)
12. Leibe, B., Schiele, B.: Scale-Invariant Object Categorization Using a ScaleAdaptive Mean-Shift Search. In: Rasmussen, C.E., Bülthoff, H.H., Schölkopf, B., Giese, M.A. (eds.) Pattern Recognition. LNCS, vol. 3175, pp. 145-153. Springer, Heidelberg (2004)
13. Dance, C., Willamowski, J., Fan, L., Bray, C., Csurka, G.: Visual categorization with bags of keypoints. In: Pajdla, T., Matas, J(G.) (eds.) ECCV 2004. LNCS, vol. 3021, Springer, Heidelberg (2004)
14. Mikolajczyk, K., Schmid, C.: A Performance Evaluation of Local Descriptors. IEEE Trans. Pattern Analysis and Machine Intelligence 27(10), 1615-1630 (2005)
15. Dorko, G., Schmid, C.: Object Class Recognition Using Discriminative Local Features. In: INRIA (2005)
16. Ullman, S., Bart, E.: Recognition invariance obtained by extended and invariant features. Neural Networks 17(1), 833-848 (2004)