Titlebook: Robust Computer Vision; Theory and Applicati Nicu Sebe,Michael S. Lew Book 2003 Springer Science+Business Media Dordrecht 2003 Active conto

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書目名稱Robust Computer Vision影響因子(影響力)




書目名稱Robust Computer Vision影響因子(影響力)學(xué)科排名




書目名稱Robust Computer Vision網(wǎng)絡(luò)公開度




書目名稱Robust Computer Vision網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Robust Computer Vision被引頻次




書目名稱Robust Computer Vision被引頻次學(xué)科排名




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書目名稱Robust Computer Vision年度引用學(xué)科排名




書目名稱Robust Computer Vision讀者反饋




書目名稱Robust Computer Vision讀者反饋學(xué)科排名

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Minatory

Introduction,ith no accompanying structural, administrative, or descriptive text information. The Internet, more specifically the Web, has become a common channel for the transmission of graphical information, thus moving visual information retrieval rapidly from stand-alone workstations and databases into a net

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Maximum Likelihood Framework,bust statistics including the outliers generation mechanisms. Further, we present the classical robust estimation procedure with an emphasis on Hampel’s approach [Hampel et al., 1986] based on influence functions. The maximum likelihood relation with other approaches is also investigated. We draw on

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Induction

alliance

Shape Based Retrieval,bject recognition, matching, registration, and analysis. Research in shape analysis has been motivated, in part, by studies of human visual form perception systems. Several theories of visual form are briefly mentioned here. A proper definition of shape similarity calls for the distinctions between

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intellect

Facial Expression Recognition,h little or no effort. Still, development of an automated system that accomplishes this task is rather difficult. There are several related problems: detection of an image segment as a face, extraction of the facial expression information, and classification of the expression (e.g., in emotion categ

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Color Based Retrieval,oints. Both the ground truth and the algorithm come from the work by Gevers and Smeulders [Gevers and Smeulders, 1999]. Furthermore, for both applications, we implement the quadratic perceptual similarity measure proposed by Hafner et al. [Hafner et al., 1995] and the correlogram introduced by Huang et al. [Huang et al., 1997] as benchmarks.