3D Face Modeling, Analysis and Recognition presentsmethodologies for analyzing shapes of facial surfaces, developscomputational tools for analyzing 3D face data, and illustratesthem using state-of-the-art applications. The methodologies chosenare based on efficient representations, metrics, comparisons, andclassifications of features that are especially relevant in thecontext of 3D measurements of human faces. These frameworks have along-term utility in face analysis, taking into account theanticipated improvements in data collection, data storage,processing speeds, and application scenarios expected as thediscipline develops further. The book covers face acquisition through 3D scanners and 3D facepre-processing, before examining the three main approaches for 3Dfacial surface analysis and recognition: facial curves; facialsurface features; and 3D morphable models. Whilst the focus ofthese chapters is fundamentals and methodologies, the algorithmsprovided are tested on facial biometric data, thereby continuallyshowing how the methods can be applied. Key features: • Explores the underlying mathematics and will apply thesemathematical techniques to 3D face analysis and recognition • Provides coverage of a wide range of applications includingbiometrics, forensic applications, facial expression analysis, andmodel fitting to 2D images • Contains numerous exercises and algorithms throughout thebook
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[ 59 ] S. Kotz , T. J. Kozubowski , and K. Podgorski , The Laplace ... valued signal processing : The proper way to deal with impropriety , ” IEEE Trans .
Some documents are annotated; some are left without annotations to provide more flexibility for instructors. This booklet can be packaged at no additional cost with any Longman title in technical communication.
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