Maria De Marsico, Michele Nappi, Daniel Riccio (auth.),'s Advances in Image and Video Technology: Third Pacific Rim 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 e-book constitutes the refereed court cases of the 3rd Pacific Rim Symposium on snapshot and Video expertise, PSIVT 2008, held in Tokyo, Japan, in January 2009.

The 39 revised complete papers and fifty seven posters have been conscientiously reviewed and chosen from 247 submissions. The symposium gains eight significant subject matters together with all features of photo and video know-how: photograph sensors and multimedia undefined; images and visualization; photograph and video research; reputation and retrieval; multi-view imaging and processing; desktop imaginative and prescient purposes; video communications and networking; and multimedia processing. The papers are equipped in topical sections on faces and pedestrians; panoramic pictures; neighborhood photo 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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Extra resources for Advances in Image and Video Technology: Third Pacific Rim Symposium, PSIVT 2009, Tokyo, Japan, January 13-16, 2009. Proceedings

Sample text

Viola et al. proposed a motion feature descriptor and combined it with cascaded AdaBoost classifier [4]. Papageorgiou et al. used SVM-based parts detectors with Haar wavelet feature and integrated them with SVM [5], [6]. Recently, using gradient-orientation-based feature descriptors, such as SIFT (Scale Invariant Feature Transform) [7] and HOG (Histograms of Oriented Gradients) [8], is a trend in object detection [9], [10]. Those feature descriptors are also used for pedestrian detection [8],[11],[12],[13].

It is interesting to note that the noFQR face recognition methods completely fail at relatively small population sizes of 100 people, whereas the FQR methods are almost unaffected. Given that the target applications for FQR assisted methods include airports and train stations where populations sizes will be in the thousands, these initial experiments present a strong case for the FQR tool’s inclusion in real-time face recognition approaches. Fig. 7 and Fig. 8 show that even for very small population sizes of up to 40 people, as soon as a face recognition method’s recognition-time approaches a second or more, significant performance degradations are observed.

This paper presents a method for visualizing a pedestrian traffic flow using results of feature point tracking. The Kanade-LucasTomasi feature tracker algorithm for point feature tracking is widely used because it is fast; however, it is sometimes fails to accurately track non-rigid objects such as pedestrians. We have developod a method of point feature tracking using a scale invariant feature transform (SIFT). Our approach uses mean-shift searching to track a point based on the information obtained by a SIFT.

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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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