Download Applied Pattern Recognition by Horst Bunke, Abraham Kandel, Mark Last PDF

By Horst Bunke, Abraham Kandel, Mark Last

A sharp raise within the computing strength of recent desktops has prompted the advance of strong algorithms which could learn complicated styles in quite a lot of facts inside a little while interval. for that reason, it has turn into attainable to use trend reputation thoughts to new projects. the most objective of this booklet is to hide a number of the most modern software domain names of development attractiveness whereas proposing novel ideas which have been built or personalized in these domains.

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Zheng. Example-based facial sketch generation with non-parametric sampling. In Proceedings of International Conference on Computer Vision, volume 2, pages 433–438, 2001 10. -Y. -H. -Y. Li. Automatic caricature generation by analyzing facial features. In Proceedings of Asian Conference on Computer Vision, 2004 11. K. A. J. L. Dipboye. Impact of large angle horizontal strabismus on ability to obtain employment. Ophthalmology, 107(2):402–405, 2000 12. U. Danino, N. Kiryati, and M. Furst. Algorithm for facial weight-change.

Human Computer Interaction, 10(4):401–444, 1995 49. M. R. Dyer. View morphing. In Proceedings of SIGGRAPH, pages 21–30, 1996 50. K. -C. Chang. Digital inpainting – survey and multilayer image inpainting algorithms. In Proceedings of International Conference on Information Technology and Applications, volume 1, pages 15–24, 2005 51. B. Smolka, K. Y. N. Plataniotis, M. Szczepanski, and K. Wojciechowski. Towards automatic redeye effect removal. Pattern Recognition Letters, 24:1767–1785, 2003 52. X.

In contrast, face reconstruction recovers in some sense the “foreground” object (face) and as such some face modeling work is certainly needed. Hwang and Lee [21] present an approach to face reconstruction. Face modeling is done by PCA on a set of prototype facial images so that the face space is spanned by the computed eigenfaces. A damaged facial image is considered as a point in a subspace spanned by reduced eigenfaces which only contain the pixels not damaged in the input image. Its optimal representation in terms of a linear combination of the reduced eigenfaces can be computed by a least square method.

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