H-Index & Metrics Best Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science D-index 157 Citations 127,286 612 World Ranking 8 National Ranking 6

Research.com Recognitions

Awards & Achievements

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)

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Computer vision
  • Statistics

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.

His most cited work include:

  • An iterative image registration technique with an application to stereo vision (10317 citations)
  • Neural network-based face detection (3348 citations)
  • Shape and motion from image streams under orthography: a factorization method (2516 citations)

What are the main themes of his work throughout his whole career to date?

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.

He most often published in these fields:

  • Artificial intelligence (70.42%)
  • Computer vision (57.95%)
  • Pattern recognition (11.86%)

What were the highlights of his more recent work (between 2008-2020)?

  • Artificial intelligence (70.42%)
  • Computer vision (57.95%)
  • Pattern recognition (11.86%)

In recent papers he was focusing on the following fields of study:

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.

Between 2008 and 2020, his most popular works were:

  • The Extended Cohn-Kanade Dataset (CK+): A complete dataset for action unit and emotion-specified expression (2042 citations)
  • Convolutional Pose Machines (1304 citations)
  • Multi-PIE (1124 citations)

In his most recent research, the most cited papers focused on:

  • Artificial intelligence
  • Computer vision
  • Statistics

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.

Best Publications

An iterative image registration technique with an application to stereo vision

Bruce D. Lucas;Takeo Kanade.
international joint conference on artificial intelligence (1981)

15866 Citations

Neural network-based face detection

H.A. Rowley;S. Baluja;T. Kanade.
IEEE Transactions on Pattern Analysis and Machine Intelligence (1998)

5856 Citations

Shape and motion from image streams under orthography: a factorization method

Carlo Tomasi;Takeo Kanade.
International Journal of Computer Vision (1992)

3721 Citations

Comprehensive database for facial expression analysis

T. Kanade;J.F. Cohn;Yingli Tian.
ieee international conference on automatic face and gesture recognition (2000)

3029 Citations

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)

1951 Citations

Recognizing action units for facial expression analysis

Y.-I. Tian;T. Kanade;J.F. Cohn.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2001)

1901 Citations

Multi-PIE

Ralph Gross;Iain Matthews;Jeffrey Cohn;Takeo Kanade.
Image and Vision Computing (2010)

1900 Citations

A statistical method for 3D object detection applied to faces and cars

H. Schneiderman;T. Kanade.
computer vision and pattern recognition (2000)

1808 Citations

A stereo matching algorithm with an adaptive window: theory and experiment

T. Kanade;M. Okutomi.
IEEE Transactions on Pattern Analysis and Machine Intelligence (1994)

1797 Citations

Limits on super-resolution and how to break them

S. Baker;T. Kanade.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2002)

1746 Citations

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