Arthur E. C. Pece, Anthony D. Worrall (auth.), Anders's Computer Vision — ECCV 2002: 7th European Conference on PDF

By Arthur E. C. Pece, Anthony D. Worrall (auth.), Anders Heyden, Gunnar Sparr, Mads Nielsen, Peter Johansen (eds.)

ISBN-10: 3540437452

ISBN-13: 9783540437451

The 4 quantity set LNCS 2350/2351/2352/2353 constitutes the refereed court cases of the seventh ecu convention on laptop imaginative and prescient, ECCV 2002, held in Copenhagen, Denmark, in may possibly 2002. The 226 revised complete papers provided have been conscientiously reviewed and chosen from a complete of round six hundred submissions. The 4 books provide topical sections on energetic and real-time imaginative and prescient, photo beneficial properties, visible movement, floor geometry, grouping and segmentation, stereoscopic imaginative and prescient, constitution from movement, form, item popularity, colour and shading, imaginative and prescient platforms, statistical studying, robotic imaginative and prescient, and calibration.

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Extra info for Computer Vision — ECCV 2002: 7th European Conference on Computer Vision Copenhagen, Denmark, May 28–31, 2002 Proceedings, Part I

Sample text

This helps us to handle the case of partial occlusion and allows us to track people and objects in a cluttered scene where no single person is isolated in any view. 2 Related Work There are numerous single-camera detection and tracking algorithms, all of which face the same difficulties of tracking 3D objects using only 2D information. These algorithms are challenged by occluding and partially-occluding objects, as well as appearance changes. Some researchers have developed multi-camera detection and tracking algorithms in order to overcome these limitations.

This scaling factor has been empirically found to give an approximately constant relationship between log-probabilities and sums of point-evaluations over a single line segment: more details are given in [16]. By this scaling, the objective function to be maximized becomes: n H= 3 1 √ h(µk | ∆I k ) Lk k=1 (13) The EM Contour Algorithm When the log-likelihood is obtained by marginalization, it is often the case that optimization by the EM method leads to more robust convergence, as compared to Newton’s method [4,13].

Cameras are located at positions surrounding the lab so that they see the objects from different viewpoints. All of the cameras are calibrated using a global coordinate system and the ground plane is also determined. Frame synchronization across cameras is achieved using a TTL-level signal generated by a Data Translation DT340 card attached to a controller PC, and transmitted via coaxial cables to all the cameras. For video acquisition, the synchronization signal is used to simultaneously start all cameras.

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Computer Vision — ECCV 2002: 7th European Conference on Computer Vision Copenhagen, Denmark, May 28–31, 2002 Proceedings, Part I by Arthur E. C. Pece, Anthony D. Worrall (auth.), Anders Heyden, Gunnar Sparr, Mads Nielsen, Peter Johansen (eds.)


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