By W. Ketchantang, S. Derrode, S. Bourennane, L. Martin (auth.), Jacques Blanc-Talon, Wilfried Philips, Dan Popescu, Paul Scheunders (eds.)
This publication constitutes the refereed court cases of the seventh overseas convention on complex options for clever imaginative and prescient platforms, ACIVS 2005, held in Antwerp, Belgium in September 2005.
The ninety revised complete papers offered have been rigorously reviewed and chosen from round 2 hundred submissions. The papers are geared up in topical sections on biometrics, category and popularity, content material and function characterization, picture and video research, photo and video coding, photograph and video segmentation, clinical snapshot processing functions, movement estimation and monitoring, noise aid and restauration, and real-time processing and hardware.
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Additional resources for Advanced Concepts for Intelligent Vision Systems: 7th International Conference, ACIVS 2005, Antwerp, Belgium, September 20-23, 2005. Proceedings
On Pattern Recognition, Brisbane (1998) 1244–1246 4. : Finger tracking as an input device for augmented reality. In: IEEE Int. Workshop on Automatic Face and Gesture Recognition, Zurich (1995) 195–200 16 S. Conseil, S. Bourennane, and L. Martin 5. : Automatic handwriting gestures recognition using hidden markov models. In: Proc. of the IEEE Int. Conf. on Automatic Face and Gesture Recognition. (2000) 6. : Real-time ﬁngertip tracking and gesture recognition. IEEE trans. on Computer Graphics and Applications 22 (2002) 64–71 7.
According to our terminology, the leading leg is the “standing” leg which at that instant carries the person’s weight (see Figures 2b and 2c). Depending on the 3D walk-direction, and on which is currently the leading leg, one leg or the other practically obscures the visible area between the legs (Figure 2a). During a walk-cycle the ratio of the areas, together with the 2D direction on the image-plane, can be used to identify which is the leading leg. During one cycle, the left leg and right leg in turn are in the leading position.
3. P. Viola and M. Jones, Rapid object detection using a boosted cascade of simple features, Proc. Int. Conf. CVPR, vol 1, pp. 511-518, 2001. 4. F. N. de With, Fast human face detection using successive face detectors with incremental detection capability, Electronic Imaging (VCIP’03) Proc. SPIE, 5022, pp. 831-841, 2003. 5. R. Duda, P. Hart, and D. , Wiley interscience, ISBN: 0-471-05669-3, 2001. 6. H. Schneiderman and T. Kanade, A statistical model for 3D object detection applied to faces and cars, Proc.
Advanced Concepts for Intelligent Vision Systems: 7th International Conference, ACIVS 2005, Antwerp, Belgium, September 20-23, 2005. Proceedings by W. Ketchantang, S. Derrode, S. Bourennane, L. Martin (auth.), Jacques Blanc-Talon, Wilfried Philips, Dan Popescu, Paul Scheunders (eds.)