Modeling visual information processing in brain: A computer vision point of view and approach

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

Volumn 4729 LNCS, Issue , 2007, Pages 62-71

  Diamant, Emanuel ^a  

^a VIDIA mant   (Israel)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; CHLORINE COMPOUNDS; COMPUTER VISION; CYBERNETICS; DIGITAL IMAGE STORAGE; IMAGING SYSTEMS; IMAGING TECHNIQUES; INFORMATION THEORY; OPTICAL DATA PROCESSING; PARALLEL PROCESSING SYSTEMS; SEMANTICS; VISUAL COMMUNICATION;

BIOLOGICAL VISIONS; COGNITIVE PROCESSING; COMPLEXITY THEORIES; HUMAN BRAINS; HUMAN OBSERVERS; IMAGE SEMANTICS; INTERNATIONAL SYMPOSIUM; KOLMOGOROV; VISUAL INFORMATION PROCESSING;

IMAGE PROCESSING;

EID: 49949112955     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-75555-5_7     Document Type: Conference Paper

References (47)

1. Diamant, E.: Does a plane imitate a bird? Does computer vision have to follow biological paradigms? In: De Gregorio, M., Di Maio, V., Frucci, M., Musio, C. (eds.) BVAI 2005. LNCS, vol. 3704, pp. 108-115. Springer, Heidelberg (2005), http://www.vidiamant.info
2. Milner, D., Goodale, M.: The Visual Brain in Action. Oxford Psychology Series, vol. 27. Oxford University Press, Oxford (1998)
3. Marr, D.: A Computational Investigation into the Human Representation and Processing of Visual Information. Freeman, San Francisco (1982)
4. Treisman, A., Gelade, G.: A feature-integration theory of attention. Cognitive Psychology 12, 97-136 (1980)
5. Biederman, I.: Recognition-by-Components: A Theory of Human Image Understanding. Psychological Review 94(2), 115-147 (1987)
6. Barsalou, L.W.: Perceptual symbol systems. Behavioral and Brain Sciences 22, 577-660 (1999)
7. Palmeri, T., Gauthier, I.: Visual Object Understanding. Nature Reviews: Neuroscience 5, 291-304 (2004)
8. Treisman, A.: The binding problem. Current Opinion in Neurobiology 6, 171-178 (1996)
9. Khefri, M.L., Ziou, D., Bernardi, A.: Image Retrieval From the World Wide Web: Issues, Techniques, and Systems. ACM Computing Surveys 36(1), 35-67 (2004)
10. Lew, M.S., Sebe, N., Djeraba, C., Jain, R.: Content-based Multimedia Information Retrieval: State of the Art and Challenges. In: ACM Transactions on Multimedia Computing, Communications, and Applications, ACM Press, New York (February 2006)
11. Mojsilovic, A., Rogowitz, B.: Capturing image semantics with low-level descriptors. In: ICIP-Ol. Proceedings of the International Conference on Image Processing, Thessaloniki, Greece, pp. 18-21 (October 2001)
12. Zhang, C., Chen, T.: From Low Level Features to High Level Semantics. In: Furht, B., Marques, O. (eds.) Handbook of Video Databases: Design and Applications, CRC Press, Boca Raton, USA (October 2003)
13. McRae, K.: Semantic Memory: Some insights from Feature-based Connectionist Attractor Networks. In: Ross, B.H. (ed.) The Psychology of Learning and Motivation, vol. 45 (2004), http://amdrae.ssc.uwo.ca/
14. Johansson, C., Lansner, A.: Attractor Memory with Self-organizing Input. In: Ijspeert, A.J., Masuzawa, T., Kusumoto, S. (eds.) BioADIT 2006. LNCS, vol. 3853, pp. 265-280. Springer, Heidelberg (2006)
15. Treue, S.: Visual attention: the where, what, how and why of saliency. Current Opinion in Neurobiology 13, 428-432 (2003)
16. Itti, L.: Models of Bottom-Up Attention and Saliency. In: Itti, L., Rees, G., Tsotsos, J. (eds.) Neurobiology of Attention, pp. 576-582. Elsevier, San Diego, CA (2005)
17. Hare, J., Lewis, P., Enser, P., Sandom, C.: Mind the Gap: Another look at the problem of the semantic gap in image retrival. In: SPIE. Proceedings of Multimedia Content Analysis, Management and Retrieval Conference, vol. 6073 (2006), http://www.ecs.soton.ac.uk/people/
18. Solomonoff, R.J.: The Discovery of Algorithmic Probability. Journal of Computer and System Science 55(1), 73-88 (1997)
19. Chaitin, G.J.: Algorithmic Information Theory. IBM Journal of Research and Development 21, 350-359 (1977)
20. Kolmogorov, A.: Three approaches to the quantitative definition of information. Problems of Information and Transmission 1(1), 1-7 (1965)
21. Floridi, L.: Trends in the Philosophy of Information. In: Adriaans, P., van Benthem, J. (eds.) Handbook of Philosophy of Information, Elsevier, Amsterdam (forthcoming), http://www.philosophyofinformation.net
22. Diamant, E.: Image information content estimation and elicitation. WSEAS Transaction on Computers 2(2), 443-448 (2003), http://www.worldses.org/journals/
23. Diamant, E.: Top-Down Unsupervised Image Segmentation (it sounds like an oxymoron, but actually it isn't). In: PRRS'04. Proceedings of the 3rd Pattern Recognition in Remote Sensing Workshop, Kingston University, UK (August 2004)
24. Diamant, E.: Searching for image information content, its discovery, extraction, and representation. Journal of Electronic Imaging 14(1) (January-March 2005)
25. Vitanyi, P.: Meaningful Information. IEEE Transactions on Information Theory 52(10), 4617-4624 (2006), http://www.cwi.nl/ paulv/papers
26. Naphade, M., Huang, T.S.: Extracting Semantics From Audiovisual Content: The Final Frontier in Multimedia Retrieval. IEEE Transactions on Neural Networks 13(4), 793-810 (2002)
27. Zhou, X.S., Huang, T.S.: CBIR: From low-Level Features to High-Level Semantics. In: Proceedings SPIE, San Jose, CA, January 24-28, 2000, vol. 3974, pp. 426-431 (2000), http://www.ifp.uiuc.edu/xzhou2/
28. Petridis, K., Kompatsiaris, I., Strintzis, M., Bloehdorn, S., Handschuh, S., Staab, S.,Simou, N., Tzouvars, V., Avrithis, Y.: Knowledge Representation for Semantic Multimedia Content Analysis and Reasoning. IEEE Transactions on CSVT 15(10), 1210-1244 (2005), http://www.iti.gr/db.php/publications
29. Diamant, E.: In Quest of Image Semantics: Are We Looking for It Under the Right Lamppost? http://arxiv.org/abs/cs.CV/0609003
30. Tuffield, M., Shadbolt, N., Millard, D.: Narratives as a Form of Knowledge Transfer: Narrative Theory and Semantics. In: Proceedings of the 1st AKT (Advance Knowledge Technologies) Symposium, Milton Keynes, UK (June 2005)
31. Franks, N., Richardson, T.: Teaching in tandem-running ants. Nature 439, 153 (2006)
32. Serre, T., Kouh, M., Cadieu, C., Knoblich, U., Kreiman, G., Poggio, T.: A theory of object recognition: computations and circuits in the feedforward path of the ventral stream in primate visual cortex, CBCL MIT paper (November 2005), http://web.mit.edu/serre/...
33. Navon, D.: Forest Before Trees: The Precedence of Global Features in Visual Perception. Cognitive Psychology 9, 353-383 (1.977)
34. Chen, L.: Topological structure in visual perception. Science 218, 699-700 (1982)
35. Navon, D.: What does a compound letter tell the psychologist's mind? Acta Psychological 14, 273-309 (2003)
36. Chen, L.: The topological approach to perceptual organization. Visual Cognition 12(4), 553-637 (2005)
37. Ahissar, M., Hochstein, S.: The reverse hierarchy theory of visual perceptual learning. Trends in Cognitive Science 8(10), 457-464 (2004)
38. Juan, C-H., Campana, G., Walsh, V.: Cortical interactions in vision and awareness: hierarchies in reverse. Progress in Brain Research 144, 117-130 (2004)
39. Hansen, T., Olkkonen, M., Walter, S., Gegenfurtner, K.: Memory modulates color appearance. Nature Neuroscience 9(11), 1367-1368 (2006)
40. Lawrence, J., Hendrickson, H.: Lateral gene transfer: when will adolescence end? Molecular Microbiology 50(3), 739-749 (2003)
41. Diba, K., Koch, C., Segev, I.: Spike propagation in dendrites with stochastic ion channels. Journal of Computational Neuroscience 20, 77-84 (2006)
42. Kandel, E.: The Molecular Biology of Memory Storage: A Dialogue Between Genes and Synapses. Science 294, 1030-1038 (2001)
43. Routtenberg, A., Rekart, J.: Post-translational protein modification as the substrate for long-lasting memory. TRENDS in Neurosciences 28(1), 12-19 (2005)
44. Kahneman, D., Treisman, A., Gibbs, B.: The reviewing of object files: Object-specific integration of information. Cognitive Psychology 24, 175-219 (1992)
45. Hommel, B.: Event files: Feature binding in and across perception and action. TRENDS in Cognitive Sciences 8(11), 494-500 (2004)
46. Waydo, S., Kraskov, A., Quiroga, R., Freid, I., Koch, C.: Sparse Representation in the Human Medial Temporal Lobe. The Journal of Neuroscience 26(40), 10232-10234 (2006)
47. European IST Research: Building on Assets, Seizing Opportunities (2005-2006),available: http://europa.eu.int/information_society/