By Muhammad Ajmal, Muhammad Husnain Ashraf, Muhammad Shakir, Yasir Abbas, Faiz Ali Shah (auth.), Leonard Bolc, Ryszard Tadeusiewicz, Leszek J. Chmielewski, Konrad Wojciechowski (eds.)
ISBN-10: 3642335632
ISBN-13: 9783642335631
ISBN-10: 3642335640
ISBN-13: 9783642335648
This publication constitutes the refereed complaints of the overseas convention on computing device imaginative and prescient and images, ICCVG 2012, held in Warsaw, Poland, in September 2012. The 89 revised complete papers provided have been conscientiously reviewed and chosen from quite a few submissions. The papers are geared up in topical sections on special effects, machine imaginative and prescient and visible surveillance.
Read Online or Download Computer Vision and Graphics: International Conference, ICCVG 2012, Warsaw, Poland, September 24-26, 2012. Proceedings PDF
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Additional info for Computer Vision and Graphics: International Conference, ICCVG 2012, Warsaw, Poland, September 24-26, 2012. Proceedings
Sample text
The drawback in our specific context comes from automatic feedbacks of the physical step that requires modifications in the surface sampling (local density change, holes, . . ) when high deformations are performed. This involves an expensive update of the mesh connections with the internal non-parameterized mesh to avoid crossed hexahedra. Finally, the discrete representation can directly use a conformal mesh and correct the self-intersections. The mesh tension can be managed with the elastic forces of a MSS for example.
209–228 (2002) 7. : Deformation Constraints in a Mass-Spring Model to Describe Rigid Cloth Behavior. In: Graphics Interface, pp. 147–154 (1996) 8. : Neck and Internal Organs, vol. 20, ch. 2. Thieme Medical Publishers (2010) 9. : Trimming local and global self-intersections in offset curves/surfaces using distance maps. In: CAD, vol. 38, pp. 183–193. Butterworth-Heinemann, Newton (2006) 10. : Theories for Mass-Spring Simulation in Computer Graphics: Stability, Costs and Improvements. IEICE - Transactions on Information and Systems E88D, 767–774 (2005) 11.
Since neurons are linear, the two-componental output of the neural network is given as y1 = ax1 + bx2 + e, y2 = cx1 + dx2 + f. Thus, the IFS consisting of n singels is represented by n ANNs, each having two linear neurons. The weights are modified using back-propagation algorithm. The error is calculated in such a way that for the given pattern the point (u1 , u2 ) 26 M. Bielecka and A. Bielecki belonging to the pattern and being the closest one to the point x1 , x2 is chosen. The error is the distance between these two points.
Computer Vision and Graphics: International Conference, ICCVG 2012, Warsaw, Poland, September 24-26, 2012. Proceedings by Muhammad Ajmal, Muhammad Husnain Ashraf, Muhammad Shakir, Yasir Abbas, Faiz Ali Shah (auth.), Leonard Bolc, Ryszard Tadeusiewicz, Leszek J. Chmielewski, Konrad Wojciechowski (eds.)
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