Hooligan Detection: the Effects of Saliency and Expert Knowledge

4th International Conference on Imaging for Crime Detection and Prevention 2011, ICDP 2011

Volumn , Issue , 2011, Pages

  Endres, D ^a   Neumann, H ^b   Kolesnik, M ^c   Giese, M A ^a  

^a UNIVERSITY HOSPITAL TÜBINGEN   (Germany)

^b UNIVERSITY OF ULM   (Germany)

^c Fraunhofer FhG FIT   (Germany)

Author keywords

Crowd monitoring; Expert knowledge; Motion patterns; Optic flow; Saliency

Indexed keywords

% REDUCTIONS; COMPUTATIONAL EFFORT; CROWD MONITORING; EXPERT KNOWLEDGE; MOTION PATTERN; NAIVE OBSERVERS; OPTIC FLOW; SALIENCY; SECURITY EXPERTS; VISUAL SEARCH;

EID: 84871790608     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (15)

1. E. Andrade, S. Blunsden, and R. Fisher. Simulation of crowd problems for computer vision. In First International Workshop on Crowd Simulation (V-CROWDS’05), Lausanne, pages 71–80, 2005.
2. P. Bayerl and H. Neumann. A fast biologically inspired algorithm for recurrent motion estimation. IEEE Transactions on Pattern Analyis and Machine Intelligence, 29(2):246–260, 2007.
3. Pierre Bayerl and Heiko Neumann. Disambiguating visual motion through contextual feedback modulation. Neural Computation, 16:2041–2066, 2004.
4. Cornelia Beck and Heiko Neumann. Interactions of motion and form in visual cortex: A neural model. Journal of Physiology - Paris, 104:61–70, 2010.
5. Christopher M. Bishop. Pattern Recognition and Machine Learning. Springer, 2007.
6. David M. Blei and Michael I. Jordan. Variational methods for the dirichlet process. In In Proceedings of the 21st International Conference on Machine Learning, 2004.
7. Jan D. Bouecke, Emilien Tlapale, Pierre Kornprobst, and Heiko Neumann. Neural mechanisms of motion detection, integration, and segregation: From biology to artificial image processing systems. EURASIP Journal on Advances in Signal Processing, 2011, 2011. Article ID 781561.
8. N. Bruce and J. Tsotsos. Saliency, attention, and visual search: An information theoretic approach. Journal of Vision, 9(3):1–24, 2009.
9. T.M. Cover and J.A. Thomas. Elements of Information Theory. Wiley, New York, 1991.
10. Navneet Dalal and Bill Triggs. Histograms of oriented gradients for human detection. In CVPR (1), pages 886–893, 2005.
11. R. Eckhorn, H.J. Reitboeck, M. Arndt, and P.W. Dicke. Feature-linking via synchronization among distributed assemblies: Simulation of results from cat cortex. Neural Computation, 2:293–307, 1990.
12. K. Lee, M. Choi, Q. Hong, and J. Lee. Group behavior from video: a data-driven approach to crowd simulation. In SCA’07: Proceedings of the 2007 ACM SIG-GRAPH/Eurographics symposium on Computer animation, pages 109–118, Aire-la-Ville, Switzerland, Switzerland, 2007. Eurographics Association.
13. J.H. Reynolds and L. Chelazzi. Attention modulation of visual processing. Annual Reviews in Neuroscience, 27:611–647, 2004.
14. J.H. Reynolds and D.J. Heeger. The normalization model of attention. Neuron, 61:168–185, 2009.
15. Eero P. Simoncelli. Bayesian multi-scale differential optical flow. In B. Jähne, H. Haussecker, and P. Geissler, editors, Handbook of Computer Vision and Applications, volume 2, chapter 14, pages 397–422. Academic Press, 1999.