Download Computer Vision – ACCV 2006: 7th Asian Conference on by Jun-Sik Kim, In So Kweon (auth.), P. J. Narayanan, Shree K. PDF

By Jun-Sik Kim, In So Kweon (auth.), P. J. Narayanan, Shree K. Nayar, Heung-Yeung Shum (eds.)

Welcometothe7thAsianConferenceonComputerVision.Itgivesusgreatpl- certain to bring about its court cases. ACCV has been making its rounds during the Asian panorama and got here to India this yr. we're happy with the technical software we've prepare and we are hoping you take pleasure in it. curiosity in laptop imaginative and prescient is expanding and ACCV 2006 attracted approximately 500 submission. The evaluate group consisted of 27 specialists serving as region Chairs and approximately 270 reviewers in all. the complete strategy was once carried out electronically in a double-blind manner,a ?rstfor ACCV. Eachpaper wasassignedto a space Chair who stumbled on 3 efficient reviewers for it. We have been capable of include the utmost load at the reviewers to 9 and the common load to below six. The overview shape had area for qualitative and quantitative assessment of the paper on 9 facets. The submitted studies underwent an intricate technique. First, they have been noticeable through the realm Chair, who resolved divergences of opinion between reviewers, if any. the realm Chair then wrote qualitative reviews and a quantitative ranking besides his/her preliminary advice at the paper. those have been checked out via software Co-chairs and compiled right into a probables record. the world Chairs and software Co-chairs met in Beijing in the course of ICCV to debate this checklist and arrivedat the ?nal record of sixty four oral papers and 128 posters. obviously, many deserving papers couldn't be accommodated.

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Additional info for Computer Vision – ACCV 2006: 7th Asian Conference on Computer Vision, Hyderabad, India, January 13-16, 2006. Proceedings, Part II

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6 Horopter The horopter of a stereo system is the set of 3D points that project to points with identical coordinates in the two cameras. Let P1 and P2 be the two cameras’ projection matrices. The horopter thus consists of all 3D points Q with P1 Q ∼ P2 Q. This is in general a quartic curve. If the two cameras have identical calibration and are separated by a fixed-axis rotation, then the horopter “degenerates” into the union of a straight line and a circle: the motion’s rotation axis and the circle in the motion plane that contains the two optical centers and that cuts the rotation axis [5].

11–20, 2006. L. Rosin, and L. Kopanja J. Zuni´ (a) (b) (c) (d) Fig. 1. Reasonable orientations of the shapes coincide with the dashed lines (a) (b) (c) (d) Fig. 2. Reasonable orientations of the shapes coincide with the dashed lines The problem becomes more complex taking into account that in computer vision and image processing tasks real shapes are replaced with their digitizations. Some specific problems arise when working with digital shapes. Let us mention just two of them: – Due to the digitization process some “non-orientable” objects may have digitizations whose orientation can be easily computed if (5) is applied.

It would be useful to see how stable the solution is. For this purpose we will define the shape orientability as a shape descriptor. The main purpose of it is to suggest an answer to the question: Is the computed orientation just a consequence of digitization or noise effects or is it an inherent property of the considered shape? The orientability can also be used as a shape descriptor in shape classification tasks. In this paper we will define an orientability measure, which is a number from [0, 1).

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