By Chrysi Papalazarou, Peter M. J. Rongen, Peter H. N. de With (auth.), Jacques Blanc-Talon, Wilfried Philips, Dan Popescu, Paul Scheunders (eds.)
This booklet constitutes the refereed complaints of the eleventh foreign convention on complex strategies for clever imaginative and prescient platforms, ACIVS 2009, held in Bordeaux, France in September/October 2009.
The forty three revised complete papers and 25 posters offered have been conscientiously reviewed and chosen from a hundred and fifteen submissions. The papers are geared up in topical sections on technovision, basic mathematical innovations, snapshot processing, coding and filtering, picture and video research, computing device imaginative and prescient, monitoring, colour, multispectral and special-purpose imaging, scientific imaging, and biometrics.
Read Online or Download Advanced Concepts for Intelligent Vision Systems: 11th International Conference, ACIVS 2009, Bordeaux, France, September 28–October 2, 2009. Proceedings PDF
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Additional resources for Advanced Concepts for Intelligent Vision Systems: 11th International Conference, ACIVS 2009, Bordeaux, France, September 28–October 2, 2009. Proceedings
Usually, the experimental research is carried out in three scales which are the laboratory, the ﬁre tunnel and the ﬁeld scales. The experiments made at these scales give entrance parameters such as the rate of spread, the physical and the geometrical characteristics of ﬂames needed for the validation of the propagation models of forest ﬁres . Several experimental methods classiﬁed in two categories have been developed. The ﬁrst group concerns discrete measures and typically consists in the use of a thermocouples set  or in the equidistant positioning of threads perpendicular to the ﬁre spread direction .
1 Principal Component Analysis (PCA) Based Systems IBISC-1&2 and BioSecure are based on the Eigenfaces approach, proposed by Turk and Pentland . The purpose of this approach is to ﬁnd the projection axes that maximize the variance of the input space. xN ], and solving the eigen problem CΦ = ΦΛ leads to the computation of an orthogonal basis Φ that describes the face space in the diﬀerent variance directions Λ. A reduced projection space is obtained by keeping the axes with the maximum of variances (highest eigenvalues), and the projected vector on the reduced space is considered as the new representation.
In our work, just two of these criteria have been considered relevant: background situation (indoor, outdoor) and background dynamism (unimodal, multimodal). A summary of the selected test sub-sequences and criteria is shown in Fig. 1. Detailed information can be found in . 1: 750,I-L 2: 750,O-H 3: 671,O-H 4: 307,O-M 5: 749,O-H 6: 749,O-L 7: 732,O-L Fig. 1. Selected test sub-sequences and criteria from the cVSG dataset. Lower data indicates sequence ID: number of frames considered, background situation (Indoor/Outdoor) – background dynamism (Low/Medium/High).