By David Van Hamme, Peter Veelaert, Wilfried Philips (auth.), Jacques Blanc-Talon, Richard Kleihorst, Wilfried Philips, Dan Popescu, Paul Scheunders (eds.)

This publication constitutes the refereed court cases of the thirteenth overseas convention on complicated techniques for clever imaginative and prescient structures, ACIVS 2011, held in Ghent, Belgium, in August 2011.

The sixty six revised complete papers offered have been conscientiously reviewed and chosen from 124 submissions. The papers are prepared in topical sections on category acceptance, and monitoring, segmentation, photographs research, photo processing, video surveillance and biometrics, algorithms and optimization; and 3D, intensity and scene understanding.

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Extra resources for Advanced Concepts for Intelligent Vision Systems: 13th International Conference, ACIVS 2011, Ghent, Belgium, August 22-25, 2011. Proceedings

Example text

In his article on the logspline density estimation theory [9], Kooperberg proposed an automatic method to place the knots according to an AIC criterion. However, preliminary experiments have convinced us that such a process is not necessary, and that a simpler strategy is more efficient. For this, we fix a given number of shot and place them according to statistic order of the learning data. For instance, if K = 9, knots are places according to the decile of data. Hence, at each dimension, the amount of information is regularly distributed between knots.

779–786 (June 2010) 16. : Fisher kernels on visual vocabularies for image categorization. In: CVPR (2007) 17. : Large-scale image retrieval with compressed fisher kernels. In: CVPR, San Francisco, USA, pp. 3384–3391 (2010) 18. : Holistic context modeling using semantic co-occurrences. In: CVPR, Los Alamitos, CA, USA, pp. 1889–1895 (2009) 19. : Scene classification with low-dimensional semantic spaces and weak supervision. In: CVPR, pp. 1–6 (2008) 20. : Video google: A text retrieval approach to object matching in videos.

First, for polynomials Bk with k > 1, we only 28 H. Le Borgne and P. Mu˜noz Fuentes consider the values y between knot tk and tk+1 , in order to avoid redundancy. The difference in equation (14) is thus computed on each interval defined by the knots. This can be seen as a sort of filter activity quantization, the limits of the cells being the knots. Secondly, for computational efficiency, we only consider the positive part (absolute value) without computing the power three. The chosen basis thus becomes: B0 (y) = 1 (not used) B1 (y) = y |y−tk |+y−tk 2 Bk>1 (y) = 0 for y < tk+1 for y > tk+1 (18) Such an implementation is equivalent to compute only (y − tk ) on the interval [tk , tk+1 ] since the polynomial is null elsewhere and y > tk on the interval.

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