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It is with nice excitement that we welcome you all to the lawsuits of the second InternationalSymposiumonVisualComputing(ISVC2006)heldinLakeTahoe. Followinga successfulmeeting lastyear,wewitnesseda muchstrongerandmore efficient occasion this 12 months. ISVC o?ers a standard umbrella for the 4 major parts of visible computing together with imaginative and prescient, snap shots, visualization, and digital fact. Its target is to supply a discussion board for researchers, scientists, engineers and practitionersthroughouttheworldtopresenttheirlatestresearch?ndings,ideas, advancements and functions within the broader zone of visible computing. This 12 months, this system consisted of thirteen oral periods, one poster consultation, ten particular tracks, and 6 keynote shows. The reaction to the decision for - pers used to be very powerful. We obtained greater than two times the papers acquired final 12 months. Speci?cally, we acquired over 280 submissions for the most symposium from which we authorised sixty five papers for oral presentation (23% recognition) and fifty six papers for poster presentation (20% acceptance). exact tune papers have been solicited individually during the Organizing and application Committees of every song. a complete of fifty seven papers have been permitted for presentation within the specified tracks. All papers have been reviewed with an emphasis on power to give a contribution to the cutting-edge within the ?eld. choice standards integrated accuracy and originality of principles, readability and signi?cance of effects, and presentation caliber. The assessment procedure was once particularly rigorous, concerning to 3 self sustaining blind reports via a number of days of dialogue. in the course of the dialogue interval we attempted to right anomalies and mistakes that will have existed within the preliminary reviews.
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Additional info for Advances in Visual Computing: Second International Symposium, ISVC 2006 Lake Tahoe, NV, USA, November 6-8, 2006 Proceedings, Part I
Rank of H is 1. In this case, both h1 and h2 are multiples of h3 . That is, h1 = c1 h3 and h2 = c2 h3 for some constants c1 and c2 . We then have ⎡ T⎤ ⎡ T ⎤ ⎡ ⎤ ⎡ ⎤ h1 h1 x c1 hT3 x c1 x = Hx = ⎣ hT2 ⎦ x = ⎣ hT2 x ⎦ = ⎣ c2 hT3 x ⎦ = (hT3 x) ⎣ c2 ⎦ . 1 hT3 hT3 x hT3 x Noting that hT3 x is a scalar, we get x = [c1 c2 1]T . Therefore, all the points of the plane in the ﬁrst image are projected onto a point in the second image. The above two degenerate cases of H are not of interest to our present discussion.
The above two degenerate cases of H are not of interest to our present discussion. Hence, we can check and then ignore these cases. Note that when the rank of H is 1 or 2, the vectors h1 , h2 , and h3 are collinear. To detect the degeneracy of H, it suﬃces to check whether hT1 (h2 × h3 ) = 0, where × is the vector cross product. 3 Segmentation Improvement We used the normalized cut algorithm to segment the image. Some of the segments are then declared planar surfaces if they contain feature points that are inliers of detected homographies.
The activity we discuss in this paper is simple activity, in the future work we will perform research on complex activity, which is a combination of a series simple activities. Acknowledgement. The authors want to thank Professor A. Hero from University of Michigan and Dr. T. Wittman from University of Minnesota for useful discussions. References 1. V. D. Shet, D. Harwood and L. S. Davis, VidMAP: Video Monitoring of Activity with Prolog, IEEE International Conference on Advanced Video and Signal based Surveillance (AVSS), Como, Italy, September 2005.