H-Index & Metrics Best Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science D-index 107 Citations 53,004 293 World Ranking 107 National Ranking 7

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Computer vision
  • Statistics

Artificial intelligence, Computer vision, Optical flow, Motion estimation and Algorithm are his primary areas of study. Artificial intelligence and Machine learning are commonly linked in his work. His Computer vision study incorporates themes from Representation, Facial expression and Affine transformation.

The study incorporates disciplines such as Flow, Iterative reconstruction, Robustness and Image processing in addition to Optical flow. His studies deal with areas such as Particle filter, Probabilistic logic and Classification of discontinuities as well as Motion estimation. His Algorithm study combines topics in areas such as Kalman filter, Outlier, Rendering and Pattern recognition.

His most cited work include:

  • A Database and Evaluation Methodology for Optical Flow (1693 citations)
  • The Robust Estimation of Multiple Motions (1388 citations)
  • Robust anisotropic diffusion (1156 citations)

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

His primary scientific interests are in Artificial intelligence, Computer vision, Optical flow, Pattern recognition and Motion. Many of his studies involve connections with topics such as Machine learning and Artificial intelligence. His study in Segmentation, Image, Image segmentation, Monocular and Motion field is carried out as part of his Computer vision studies.

His Optical flow research is multidisciplinary, incorporating elements of Flow, Algorithm, Pixel and Robustness. His work focuses on many connections between Pattern recognition and other disciplines, such as Representation, that overlap with his field of interest in Polygon mesh. His research combines Affine transformation and Motion estimation.

He most often published in these fields:

  • Artificial intelligence (77.15%)
  • Computer vision (52.33%)
  • Optical flow (16.95%)

What were the highlights of his more recent work (between 2017-2021)?

  • Artificial intelligence (77.15%)
  • Computer vision (52.33%)
  • Artificial neural network (7.13%)

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

Michael J. Black focuses on Artificial intelligence, Computer vision, Artificial neural network, Motion and Motion capture. His study in Artificial intelligence is interdisciplinary in nature, drawing from both Code and Pattern recognition. His research integrates issues of Optical flow, Representation and Task in his study of Pattern recognition.

In his work, Gesture is strongly intertwined with Deep learning, which is a subfield of Computer vision. The various areas that Michael J. Black examines in his Motion study include Polygon mesh, Inference, Motion analysis and Body shape. His Motion capture research is multidisciplinary, relying on both 3D pose estimation, Cognitive psychology and Inertial measurement unit.

Between 2017 and 2021, his most popular works were:

  • End-to-End Recovery of Human Shape and Pose (660 citations)
  • Recovering Accurate {3D} Human Pose in the Wild Using {IMUs} and a Moving Camera (203 citations)
  • Expressive Body Capture: 3D Hands, Face, and Body From a Single Image (195 citations)

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

  • Artificial intelligence
  • Computer vision
  • Statistics

His primary areas of investigation include Artificial intelligence, Computer vision, Artificial neural network, Ground truth and Face. His Artificial intelligence research includes elements of Polygon mesh and Code. His Motion capture, Monocular, Pixel, Image and Inertial measurement unit investigations are all subjects of Computer vision research.

Michael J. Black has included themes like Computer engineering, Eye tracking, Optical flow, Robot and Robustness in his Artificial neural network study. His Optical flow study incorporates themes from Image resolution, Pyramid and Unsupervised learning, Pattern recognition. In Face, Michael J. Black works on issues like RGB color model, which are connected to Facial expression.

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

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 Robust Estimation of Multiple Motions

Michael J. Black;P. Anandan.
Computer Vision and Image Understanding (1996)

2257 Citations

Robust anisotropic diffusion

M.J. Black;G. Sapiro;D.H. Marimont;D. Heeger.
IEEE Transactions on Image Processing (1998)

1752 Citations

Secrets of optical flow estimation and their principles

Deqing Sun;Stefan Roth;Michael J. Black.
computer vision and pattern recognition (2010)

1479 Citations

EigenTracking: Robust Matching and Tracking of Articulated Objects Using a View-Based Representation

Michael J. Black;Allan D. Jepson.
International Journal of Computer Vision (1998)

1320 Citations

Fields of Experts: a framework for learning image priors

S. Roth;M.J. Black.
computer vision and pattern recognition (2005)

1087 Citations

A naturalistic open source movie for optical flow evaluation

Daniel J. Butler;Jonas Wulff;Garrett B. Stanley;Michael J. Black.
european conference on computer vision (2012)

1085 Citations

HumanEva: Synchronized Video and Motion Capture Dataset and Baseline Algorithm for Evaluation of Articulated Human Motion

Leonid Sigal;Alexandru O. Balan;Michael J. Black.
International Journal of Computer Vision (2010)

1012 Citations

Stochastic Tracking of 3D Human Figures Using 2D Image Motion

Hedvig Sidenbladh;Michael J. Black;David J. Fleet.
european conference on computer vision (2000)

970 Citations

On the unification of line processes, outlier rejection, and robust statistics with applications in early vision

Michael J. Black;Anand Rangarajan.
International Journal of Computer Vision (1996)

843 Citations

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