H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science H-index 57 Citations 34,029 111 World Ranking 1853 National Ranking 1017

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Computer vision
  • Machine learning

Artificial intelligence, Computer vision, Facial recognition system, Pattern recognition and Active appearance model are his primary areas of study. His Artificial intelligence study frequently draws parallels with other fields, such as Flow. Simon Baker works mostly in the field of Computer vision, limiting it down to concerns involving Database and, occasionally, Computer graphics.

His Facial recognition system research is under the purview of Face. His studies deal with areas such as 3D reconstruction and Motion capture as well as Pattern recognition. His Active appearance model research is multidisciplinary, relying on both Object and Inverse.

His most cited work include:

  • Lucas-Kanade 20 Years On: A Unifying Framework (2508 citations)
  • A Database and Evaluation Methodology for Optical Flow (1693 citations)
  • The CMU pose, illumination, and expression database (1550 citations)

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

Simon Baker mainly investigates Artificial intelligence, Computer vision, Facial recognition system, Active appearance model and Pattern recognition. While working on this project, Simon Baker studies both Artificial intelligence and Parametric model. His research is interdisciplinary, bridging the disciplines of Computer graphics and Computer vision.

He interconnects Contextual image classification, Machine learning and Data modeling in the investigation of issues within Facial recognition system. The various areas that Simon Baker examines in his Active appearance model study include Image registration and Facial motion capture. In his research on the topic of Pattern recognition, Algorithm is strongly related with Cognitive neuroscience of visual object recognition.

He most often published in these fields:

  • Artificial intelligence (80.95%)
  • Computer vision (61.11%)
  • Facial recognition system (23.02%)

What were the highlights of his more recent work (between 2011-2017)?

  • Artificial intelligence (80.95%)
  • Computer vision (61.11%)
  • Information retrieval (5.56%)

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

His primary scientific interests are in Artificial intelligence, Computer vision, Information retrieval, Image and Boiling. His work in the fields of Artificial intelligence, such as Facial recognition system and Contextual image classification, overlaps with other areas such as Identification system. Simon Baker combines subjects such as Machine learning, Cloud computing and Global Positioning System with his study of Facial recognition system.

The concepts of his Computer vision study are interwoven with issues in Speech recognition and Curve matching. His Information retrieval research is multidisciplinary, incorporating perspectives in Metadata and World Wide Web. His studies in Boiling integrate themes in fields like Natural convection and Free surface.

Between 2011 and 2017, his most popular works were:

  • Recognizing proxemics in personal photos (76 citations)
  • Car make and model recognition using 3D curve alignment (51 citations)
  • Setting an operating-system color using a photograph (33 citations)

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

  • Artificial intelligence
  • Computer vision
  • Machine learning

Simon Baker spends much of his time researching Artificial intelligence, Computer vision, Image, Set and Curve matching. Artificial intelligence is closely attributed to Operating system in his study. Simon Baker has researched Operating system in several fields, including Pixel, Color depth, High color and Computer graphics.

Borrowing concepts from Filter, Simon Baker weaves in ideas under Computer vision. His research integrates issues of Metadata and Information retrieval in his study of Sentence generation. His biological study spans a wide range of topics, including Training set, Active appearance model and Visual hull.

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.

Top Publications

The CMU Pose, Illumination, and Expression (PIE) database

T. Sim;S. Baker;M. Bsat.
ieee international conference on automatic face and gesture recognition (2002)

3888 Citations

Lucas-Kanade 20 Years On: A Unifying Framework

Simon Baker;Iain Matthews.
International Journal of Computer Vision (2004)

3485 Citations

A Database and Evaluation Methodology for Optical Flow

Simon Baker;Daniel Scharstein;J. P. Lewis;Stefan Roth.
International Journal of Computer Vision (2011)

2706 Citations

The CMU pose, illumination, and expression database

T. Sim;S. Baker;M. Bsat.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2003)

2520 Citations

Active Appearance Models Revisited

Iain Matthews;Simon Baker.
International Journal of Computer Vision (2004)

2171 Citations

Multi-PIE

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

1900 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

The template update problem

L. Matthews;T. Ishikawa;S. Baker.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2004)

1110 Citations

A Theory of Single-Viewpoint Catadioptric Image Formation

Simon Baker;Shree K. Nayar.
International Journal of Computer Vision (1999)

846 Citations

Hallucinating faces

S. Baker;T. Kanade.
ieee international conference on automatic face and gesture recognition (2000)

728 Citations

Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking h-index is inferred from publications deemed to belong to the considered discipline.

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