An approach to supervised training of document-specific character templates from sample page images and unaligned transcriptions is presented. The template estimation problem is formulated as one of constrained maximum likelihoodparameter estimation within the document image decoding (DID) framework. This leads to a two-phase iterative training algorithm consisting of transcriptionalignment and...

This paper proposes a real-time head pose estimation system usinga new image matchingtechnique. The system consists ofa trainingstage,in which subspace dictionaries for classifyinghead poses are computed using template matchingand the factorization method, and a recognition stage,in which head poses are estimated usingthe subspace method. The system uses the method ofadaptivelyscaled template m...

This paper presents an automatic FDP (Facial Definition Parameters) and FAP (Facial Animation Parameters) generation method from an image sequence that captures a frontal face. The proposed method is based on facial feature tracking without markers on a face. We present an efficient method to extract 2D facial features and to generate the FDP by applying 2D features to a generic face model. We ...

A central notion in Computational Anatomy is the generation of registration maps,mapping a large set of anatomical data to a common coordinate system to study intra-population variability and inter-population differences. In previous work [1, 2] methods for estimating the common coordinate system or the template given a collection imaging data were presented based on the notion of Fréchet mean ...

Template Estimation 1 Gary E. Kopec2 Xerox Palo Alto Research Center Mauricio Lomelin3 Microsoft Corp. November 29, 1995 Abstract This paper develops an approach to supervised training of character templates from page images and unaligned transcriptions. The template estimation problem is formulated as one of constrained maximum likelihood parameter estimation within the document image decoding...