By Michael Hödlmoser, Martin Kampel (auth.), George Bebis, Richard Boyle, Bahram Parvin, Darko Koracin, Ronald Chung, Riad Hammound, Muhammad Hussain, Tan Kar-Han, Roger Crawfis, Daniel Thalmann, David Kao, Lisa Avila (eds.)
It is with nice excitement that we current the lawsuits of the sixth Inter- tional, Symposium on visible Computing (ISVC 2010), which was once held in Las Vegas, Nevada. ISVC presents a standard umbrella for the 4 major components of visible computing together with imaginative and prescient, snap shots, visualization, and digital fact. The target is to supply a discussion board for researchers, scientists, engineers, and pr- titioners in the course of the international to give their most recent learn ?ndings, rules, advancements, and purposes within the broader zone of visible computing. This yr, this system consisted of 14 oral periods, one poster consultation, 7 specific tracks, and six keynote shows. The reaction to the decision for papers used to be first-class; we acquired over three hundred submissions for the most symposium from which we accredited ninety three papers for oral presentation and seventy three papers for poster p- sentation. specified song papers have been solicited individually throughout the Organizing and software Committees of every tune. a complete of forty four papers have been authorized for oral presentation and six papers for poster presentation within the certain tracks.
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Additional info for Advances in Visual Computing: 6th International Symposium, ISVC 2010, Las Vegas, NV, USA, November 29 – December 1, 2010, Proceedings, Part II
C) Estimated arcs. 75. 79212. 5 Ransac−Taubin−LM Ransac−Taubin Ransac −8 10 −7 10 −6 10 0 −1e−009 −1e−008 −1e−007 Varying lambda −1e−006 −1e−005 (b) Fig. 2. Results of synthetic image experiments with varying λ. Distortion center is ﬁxed at image center (x0 , y0 ) = (320, 240). (a) Noise in the undistorted image relative to the original image, measured by the ratio of the RMSE using estimated parameters to the RMSE using true parameters. (b) Error in estimating λ. Each point is an average over the same 10 runs shown in part (a).
Beardsley ﬁrst described the extraction of intrinsic camera parameters from three VPs in . By the determination of three VPs within one image, the principal point and the focal length can be recovered sequentially. In , camera calibration using three VPs of an image is described. Their semiautomatic auto-calibration method uses building facades to determine three VPs. The user needs to select a set of parallel image lines in order to search for correct VP initialization. After initialization, the intrinsic parameters are recovered.
1 Introduction Most computer vision algorithms, particularly structure from motion algorithms, rely on the assumption of a linear pinhole camera model. However, most commercially available cameras introduce suﬃciently severe optical distortion that the pinhole assumption is invalid, making distortion correction a must. Radial distortion is the most signiﬁcant type of distortion in today’s cameras [1,2]. It is most evident in images produced with low-cost, wide-angle lenses. Such lenses are being widely deployed, for example, in automotive applications such as assisting drivers to view a vehicle’s blind spots [3,4].
Advances in Visual Computing: 6th International Symposium, ISVC 2010, Las Vegas, NV, USA, November 29 – December 1, 2010, Proceedings, Part II by Michael Hödlmoser, Martin Kampel (auth.), George Bebis, Richard Boyle, Bahram Parvin, Darko Koracin, Ronald Chung, Riad Hammound, Muhammad Hussain, Tan Kar-Han, Roger Crawfis, Daniel Thalmann, David Kao, Lisa Avila (eds.)