2012 - Fellow of the International Association for Pattern Recognition (IAPR) For contributions to the development of statistical models of shape and appearance.
His scientific interests lie mostly in Artificial intelligence, Active appearance model, Computer vision, Active shape model and Pattern recognition. His Active appearance model study which covers Robustness that intersects with Statistical shape analysis and Iterative refinement. His Computer vision research is multidisciplinary, incorporating perspectives in Range and Pattern recognition.
His work carried out in the field of Active shape model brings together such families of science as Active contour model, Point distribution model, Statistical model, Algorithm and Point. The Statistical model study combines topics in areas such as Matching and Image segmentation. His biological study spans a wide range of topics, including Orientation, Pixel, Regression and Blossom algorithm.
His main research concerns Artificial intelligence, Computer vision, Pattern recognition, Active appearance model and Image. In general Artificial intelligence, his work in Active shape model, Statistical model, Face and Facial recognition system is often linked to Set linking many areas of study. His biological study deals with issues like Algorithm, which deal with fields such as Shape analysis.
His Computer vision study frequently involves adjacent topics like Pattern recognition. The study incorporates disciplines such as Object, Pixel, Random forest and Matching in addition to Pattern recognition. His Active appearance model research includes themes of Image texture, Matching and Vertebra.
Timothy F. Cootes mostly deals with Artificial intelligence, Radiography, Random forest, Pattern recognition and Orthodontics. The concepts of his Artificial intelligence study are interwoven with issues in Machine learning and Computer vision. His Radiography research incorporates elements of Physical therapy, Wrist and Computer-aided diagnosis.
His Random forest study incorporates themes from Backpropagation, False positive paradox and Cohen's kappa. His work deals with themes such as Image, CAD and Computed tomography, which intersect with Pattern recognition. His studies in Orthodontics integrate themes in fields like Cross-sectional study, Connection and Hip pain.
Radiography, Artificial intelligence, Random forest, Fully automatic and Pattern recognition are his primary areas of study. Timothy F. Cootes has researched Radiography in several fields, including Algorithm, Physical therapy and Wrist. His Artificial intelligence research is multidisciplinary, relying on both Node and Computer vision.
Timothy F. Cootes is involved in the study of Computer vision that focuses on Image in particular. His Random forest research incorporates elements of Tree, Sample, Binary decision diagram and Decision tree. His studies in Pattern recognition integrate themes in fields like Coronal plane and Maximally stable extremal regions.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
Active shape models—their training and application
T. F. Cootes;C. J. Taylor;D. H. Cooper;J. Graham.
Computer Vision and Image Understanding (1995)
Active appearance models
T.F. Cootes;G.J. Edwards;C.J. Taylor.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2001)
Use of active shape models for locating structures in medical images
Timothy F. Cootes;Andrew Hill;Christopher J. Taylor;J. Haslam.
Image and Vision Computing (1994)
Active shape models - 'Smart Snakes'.
Timothy F. Cootes;Christopher J. Taylor.
british machine vision conference (1992)
Automatic interpretation and coding of face images using flexible models
A. Lanitis;C.J. Taylor;T.F. Cootes.
IEEE Transactions on Pattern Analysis and Machine Intelligence (1997)
Toward automatic simulation of aging effects on face images
A. Lanitis;C.J. Taylor;T.F. Cootes.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2002)
Feature Detection and Tracking with Constrained Local Models
David Cristinacce;Timothy F. Cootes.
british machine vision conference (2006)
Training models of shape from sets of examples
Timothy F. Cootes;Christopher J. Taylor;David H. Cooper;Jim Graham.
british machine vision conference (1992)
Interpreting face images using active appearance models
G.J. Edwards;C.J. Taylor;T.F. Cootes.
ieee international conference on automatic face and gesture recognition (1998)
View-based active appearance models
Timothy F. Cootes;Gavin V. Wheeler;Kevin N. Walker;Christopher J. Taylor.
Image and Vision Computing (2002)
Profile was last updated on December 6th, 2021.
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