Advances in Image and Video Technology: Third Pacific Rim by Maria De Marsico, Michele Nappi, Daniel Riccio (auth.), PDF

By Maria De Marsico, Michele Nappi, Daniel Riccio (auth.), Toshikazu Wada, Fay Huang, Stephen Lin (eds.)

ISBN-10: 3540929568

ISBN-13: 9783540929567

ISBN-10: 3540929576

ISBN-13: 9783540929574

This publication constitutes the refereed complaints of the 3rd Pacific Rim Symposium on snapshot and Video know-how, PSIVT 2008, held in Tokyo, Japan, in January 2009.

The 39 revised complete papers and fifty seven posters have been rigorously reviewed and chosen from 247 submissions. The symposium gains eight significant subject matters together with all points of photo and video know-how: picture sensors and multimedia undefined; pics and visualization; photograph and video research; acceptance and retrieval; multi-view imaging and processing; laptop imaginative and prescient purposes; video communications and networking; and multimedia processing. The papers are prepared in topical sections on faces and pedestrians; panoramic pictures; neighborhood snapshot research; association and grouping; multiview geometry; detection and monitoring; computational images and forgeries; coding and steganography; acceptance and seek; and reconstruction and visualization.

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This publication constitutes the refereed complaints of the 3rd Pacific Rim Symposium on photo and Video know-how, PSIVT 2008, held in Tokyo, Japan, in January 2009. The 39 revised complete papers and fifty seven posters have been rigorously reviewed and chosen from 247 submissions. The symposium positive aspects eight significant issues together with all points of snapshot and video expertise: snapshot sensors and multimedia undefined; pix and visualization; photo and video research; acceptance and retrieval; multi-view imaging and processing; desktop imaginative and prescient purposes; video communications and networking; and multimedia processing.

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Extra info for Advances in Image and Video Technology: Third Pacific Rim Symposium, PSIVT 2009, Tokyo, Japan, January 13-16, 2009. Proceedings

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Fig. 1. The new face recognition system tests the face quality before recognition is attempted FQR pre-filtering at this stage offers many advantages over conventional face recognition systems: 1. The final face recognition stage can be avoided for a face image with a low FQR. This saves on the recognition-time expense for an image that is probably unrecognizable. 2. The final face recognition stage can be delayed until a better quality image of that face is captured, thereby improving the probability of success.

3) Then the spatial mean-shift vector is obtained as È ÈK N i=0 Δx = loc (xi − x, σxy )ω(xi , s)(xi − N i=0 Kloc (xi − x, σxy )ω(xi , s) x0 ) , (4) where Kloc is a spatial kernel function given by Kloc (x, σxy ) = exp −(x2 + y 2 ) 2 2σxy . (5) Finally, we can get the new location x = x + Δx from the mean-shift vector as shown in Figure 3(a). Step2 Mean-Shift in Scale Space Our approach uses a mean-shift procedure to estimate the scale parameter of the keypoint at the location obtained in step1.

The scale is updated by s = sΔS using the mean-shift vector ΔS in scale space. Step3 Iteration Iterate by interleaving steps 1 and 2 until both |Δx| < xy and |ΔS − 1| < S. Rejection of Tracking Failure Point. Our keypoint tracker sometimes loses features when they became occluded or leave an image. To make a decision whether a feature is lost or not, we compute the Euclidean distance of the SIFT features at the new location x , and previous location x using equation (2). If the distance is above a given threshold, the keypoint at the new location x is deemed a lost feature point and rejected.

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Advances in Image and Video Technology: Third Pacific Rim Symposium, PSIVT 2009, Tokyo, Japan, January 13-16, 2009. Proceedings by Maria De Marsico, Michele Nappi, Daniel Riccio (auth.), Toshikazu Wada, Fay Huang, Stephen Lin (eds.)


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