Download e-book for kindle: Advances on Digital Television and Wireless Multimedia by Chao Jiang, Ze-xun Geng, Xiao-feng Wei, Chen Shen (auth.),

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By Chao Jiang, Ze-xun Geng, Xiao-feng Wei, Chen Shen (auth.), Wenjun Zhang, Xiaokang Yang, Zhixiang Xu, Ping An, Qizhen Liu, Yue Lu (eds.)

ISBN-10: 3642345948

ISBN-13: 9783642345944

ISBN-10: 3642345956

ISBN-13: 9783642345951

This ebook constitutes the refereed lawsuits of the ninth overseas discussion board on electronic television and instant Multimedia verbal exchange, IFTC 2012, Shanghai, China, November. The sixty nine revised complete papers awarded have been conscientiously reviewed and chosen from a number of submissions. The papers are geared up in topical sections on photo processing and trend attractiveness; snapshot and video research; photo caliber evaluation; textual content photograph and speech processing; content material retrieval and protection; resource coding; multimedia conversation; new advances in broadband multimedia; human machine interface; 3D video.

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Additional resources for Advances on Digital Television and Wireless Multimedia Communications: 9th International Forum on Digital TV and Wireless Multimedia Communication, IFTC 2012, Shanghai, China, November 9-10, 2012. Proceedings

Sample text

Before this, we qualify the average error of kNNF as n2 k M SE(A(x), B(x + fi (x))/kn2 E= (3) x=1 i=1 where M SE is the standard function for computing mean squared error between two patches located at x in image A and x + fi (x) in image B, n2 is the amount of effective patches in image A. To intuitively compare the matching error of our algorithm with the one of Barnes’s algorithm, a most recently benchmark algorithm, the second criterion error rate (ER) is defined as ER = E/E0 (4) where E and E0 are the average errors of new algorithm and the original Barnes’s, respectively.

In our system, we set a magnitude threshold for the residual vectors. Those SURF pairs whose residual vector magnitudes are greater than the threshold are assumed to belong to the region of moving objects. As for multiple moving objects, we categorize these dominant residual vectors and obtain local motion distribution using k-means method. Motion compensation for camera shaking and moving objects can be conducted by six steps: 1) Extract SURF points and descriptors for two successive LDR images, and find the best matched pairs between them; 2) Randomly select three pairs of matched points whose location vectors are independent with each other, and calculate the transformation matrix Cj; 3) Iterate the second step for m times, and use RANSAC method to find the most accurate transformation matrix C; 4) Compensate global motion using matrix C.

They use the information recorded in the sequence of differently exposed LDR images or even a single LDR image to reconstruct a so-called HDR image like the Apple iPhones, which indeed has the same dynamic range as LDR images but only enhanced in visual quality [1]. These works are very useful in the W. Zhang et al. ): IFTC 2012, CCIS 331, pp. 29–36, 2012. © Springer-Verlag Berlin Heidelberg 2012 30 T. Zhao and Y. Xu situations where visual effects are most concerned about. However, these works would be unavailable when we need the radiance maps of the captured scenes for analysis or display on some advanced HDR display devices.

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Advances on Digital Television and Wireless Multimedia Communications: 9th International Forum on Digital TV and Wireless Multimedia Communication, IFTC 2012, Shanghai, China, November 9-10, 2012. Proceedings by Chao Jiang, Ze-xun Geng, Xiao-feng Wei, Chen Shen (auth.), Wenjun Zhang, Xiaokang Yang, Zhixiang Xu, Ping An, Qizhen Liu, Yue Lu (eds.)


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