Large-scale real-time object identification based on analytic features

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

Volumn 5769 LNCS, Issue PART 2, 2009, Pages 663-672

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

^a HONDA RESEARCH INSTITUTE EUROPE GMBH   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

CHARACTERISTIC VIEWS; FIGURE-GROUND; OBJECT IDENTIFICATION;

BACKPROPAGATION; FEATURE EXTRACTION;

NEURAL NETWORKS;

EID: 70450183235     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-04277-5_67     Document Type: Conference Paper

References (15)

1. Turk, M., Pentland, A.: Eigenfaces for Recognition. Journal of Cognitive Neuroscience 3(1), 71-86 (1991)
2. Wersing, H., Körner, E.: Learning Optimized Features for Hierarchical Models of Invariant Object Recognition. Neural Computation 15(7), 1559-1588 (2003)
3. Lowe, D.G.: Distinctive Image Features from Scale-Invariant Keypoints. International Journal of Computer Vision 60(2), 91-110 (2004)
4. Hasler, S., Wersing, H., Körner, E.: A comparison of features in parts-based object recognition hierarchies. In: Artificial Neural Networks - ICANN, pp. 210-219 (2007)
5. Serre, T., Oliva, A., Poggio, T.: A feedforward architecture accounts for rapid categorization. Proc. of the National Academy of Science, 6424-6429 (2007)
6. Tanaka, K.: Inferotemporal Cortex And Object Vision. Annual Review of Neuroscience 19, 109-139 (1996)
7. 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)
8. Kim, H., Chutorian, E.M., Triesch, J.: Semi-autonomous learning of objects. In: IEEE CVPR Workshop: Vision for Human-Computer Interaction, vol. 145 (2006)
9. Goerick, C., Mikhailova, I., Wersing, H., Kirstein, S.: Biologically motivated visual behaviours for humanoids: Learning to interact and learning in interaction. In: Proc. IEEE/RSJ Int. Conf. on Humanoid Robots, Tsukuba, Japan (2006)
10. Denecke, A., Wersing, H., Steil, J.J., Körner, E.: Online figure-ground segmentation with adaptive metrics in generalized LVQ. Neurocomputing 72(7-9), 1470-1482 (2009)
11. Swain, M.J., Ballard, D.H.: Color indexing. International Journal of Computer Vision 7(1), 11-32 (1991)
12. Pomierski, T., Gross, H.M.: Biological neural architecture for chromatic adaptation resulting in constant color sensations. In: IEEE International Conference on Neural Networks, pp. 734-739 (1996)
13. Bolder, B., Dunn, M., Gienger, M., Janssen, H., Sugiura, H., Goerick, C.: Visually guided whole body interaction. In: IEEE International Conference on Robotics and Automation (2007)
14. Nayar, S.K., Nene, S.A., Murase, H.: Real-time 100 object recognition system. In: Proc. IEEE Conference on Robotics and Automation, vol. 3, pp. 2321-2325 (1996)
15. Munich, M.E., Pirjanian, P., Bernardo, E.D., Goncalves, L., Karlsson, N., Lowe, D.G.: SIFT-ing through features with ViPR: Application of visual pattern recognition to robotics and automation. IEEE Robotics and Autom. Mag., 72-77 (2006)