2017 - IEEE Founders Medal For pioneering and seminal contributions to computer vision and robotics for automotive safety
2010 - ACM AAAI Allen Newell Award For fundamental contributions to research in computer vision and robotics, for applications to driving, 3D vision and quality of life technology, and for promoting the interaction between computer science and other disciplines, most notably robotics.
2008 - Benjamin Franklin Medal, Franklin Institute
2004 - Fellow of the American Academy of Arts and Sciences
1999 - ACM Fellow For broad contributions to research in and the advancement of computer science and robotics, and for service to the ACM and the greater computer science and robotics community.
1997 - Member of the National Academy of Engineering For contributions to computer vision and robotics.
1992 - IEEE Fellow For contributions to vision, manipulators, autonomous mobile robots, and sensors.
1990 - Fellow of the Association for the Advancement of Artificial Intelligence (AAAI)
The scientist’s investigation covers issues in Artificial intelligence, Computer vision, Pattern recognition, Facial recognition system and Image processing. Artificial intelligence is represented through his Pixel, Face detection, Feature extraction, Facial expression and Face research. His work deals with themes such as Stereopsis, Segmentation and Interpolation, which intersect with Pixel.
His Computer vision research includes elements of Computer graphics and Pattern recognition. His work focuses on many connections between Pattern recognition and other disciplines, such as Object, that overlap with his field of interest in Viola–Jones object detection framework. Takeo Kanade has included themes like Matching, Algorithm, Line and Invariant in his Image processing study.
Takeo Kanade mainly investigates Artificial intelligence, Computer vision, Pattern recognition, Image processing and Computer graphics. His Artificial intelligence study focuses mostly on Pixel, Robotics, Image, Object and Motion estimation. His study ties his expertise on Robustness together with the subject of Computer vision.
Takeo Kanade works mostly in the field of Pattern recognition, limiting it down to topics relating to Facial recognition system and, in certain cases, Facial expression. His study connects Pattern recognition and Image processing. His research on Computer graphics frequently links to adjacent areas such as Virtual reality.
Takeo Kanade mainly focuses on Artificial intelligence, Computer vision, Pattern recognition, Image segmentation and Feature extraction. Image, Image processing, Segmentation, Pixel and Feature are among the areas of Artificial intelligence where the researcher is concentrating his efforts. His studies in Computer vision integrate themes in fields like Robot, Robustness and Microscopy.
He has researched Pattern recognition in several fields, including Contextual image classification, Supervised learning and Cluster analysis. His Image segmentation research focuses on Image restoration and how it connects with Image formation. His work carried out in the field of Feature extraction brings together such families of science as Video tracking and Feature detection.
Takeo Kanade spends much of his time researching Artificial intelligence, Computer vision, Pattern recognition, Feature extraction and Image segmentation. His research in Feature, Pose, Active appearance model, Image processing and Segmentation are components of Artificial intelligence. His Computer vision study integrates concerns from other disciplines, such as Software and Robustness.
The various areas that Takeo Kanade examines in his Pattern recognition study include Object, Initialization and Solid modeling. His research integrates issues of Feature detection, Stem cell, Visualization, Hidden Markov model and Search algorithm in his study of Feature extraction. The study incorporates disciplines such as Anisotropic diffusion, Maximization, Pixel, Approximation algorithm and Thresholding in addition to Image segmentation.
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.
An iterative image registration technique with an application to stereo vision
Bruce D. Lucas;Takeo Kanade.
international joint conference on artificial intelligence (1981)
Neural network-based face detection
H.A. Rowley;S. Baluja;T. Kanade.
IEEE Transactions on Pattern Analysis and Machine Intelligence (1998)
Shape and motion from image streams under orthography: a factorization method
Carlo Tomasi;Takeo Kanade.
International Journal of Computer Vision (1992)
Comprehensive database for facial expression analysis
T. Kanade;J.F. Cohn;Yingli Tian.
ieee international conference on automatic face and gesture recognition (2000)
A System for Video Surveillance and Monitoring
Robert T. Collins;Alan J. Lipton;Takeo Kanade;Hironobu Fujiyoshi.
VSAM Final Report by Robotics Institute of CMU (2000)
Recognizing action units for facial expression analysis
Y.-I. Tian;T. Kanade;J.F. Cohn.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2001)
Ralph Gross;Iain Matthews;Jeffrey Cohn;Takeo Kanade.
Image and Vision Computing (2010)
A statistical method for 3D object detection applied to faces and cars
H. Schneiderman;T. Kanade.
computer vision and pattern recognition (2000)
A stereo matching algorithm with an adaptive window: theory and experiment
T. Kanade;M. Okutomi.
IEEE Transactions on Pattern Analysis and Machine Intelligence (1994)
Limits on super-resolution and how to break them
S. Baker;T. Kanade.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2002)
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