What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Computer vision
- Algorithm
His primary scientific interests are in Artificial intelligence, Computer vision, Texture, Motion estimation and Motion field.
Many of his research projects under Artificial intelligence are closely connected to Set with Set, tying the diverse disciplines of science together.
James R. Bergen has researched Computer vision in several fields, including Visual perception and Perception.
His study explores the link between Texture and topics such as Geometry that cross with problems in Texture segregation and Early vision.
His Motion estimation research is multidisciplinary, relying on both Motion compensation and Pose.
His work deals with themes such as Motion detection, Illusory motion and Structure from motion, which intersect with Motion field.
His most cited work include:
- Spatiotemporal energy models for the perception of motion (3018 citations)
- Hierarchical Model-Based Motion Estimation (1240 citations)
- The Plenoptic Function and the Elements of Early Vision (1170 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of study are Artificial intelligence, Computer vision, Computer graphics, Geography and Motion.
James R. Bergen integrates many fields in his works, including Computer vision and Process.
His Motion study combines topics in areas such as Algorithm and Optics.
His Algorithm study combines topics from a wide range of disciplines, such as Translation and Affine transformation.
His Orientation study integrates concerns from other disciplines, such as Texture and Perception.
James R. Bergen is studying Motion field, which is a component of Motion estimation.
He most often published in these fields:
- Artificial intelligence (81.03%)
- Computer vision (79.31%)
- Computer graphics (15.52%)
What were the highlights of his more recent work (between 2004-2019)?
- Artificial intelligence (81.03%)
- Computer vision (79.31%)
- Geography (18.97%)
In recent papers he was focusing on the following fields of study:
James R. Bergen spends much of his time researching Artificial intelligence, Computer vision, Geography, Iris image and Iris.
His work on Artificial intelligence deals in particular with Digital image, Iris recognition, Biometrics, Iris code and Camera auto-calibration.
His Computer vision research includes themes of Computer graphics and Identification.
His work carried out in the field of Computer graphics brings together such families of science as Pyramid, Video camera and Video processing.
The various areas that James R. Bergen examines in his Orientation study include Epipolar geometry, Real image and Parallax.
His work on Feature detection as part of general Image processing study is frequently connected to Multiple sensors, therefore bridging the gap between diverse disciplines of science and establishing a new relationship between them.
Between 2004 and 2019, his most popular works were:
- Visual odometry for ground vehicle applications (568 citations)
- Methods and systems for biometric identification (75 citations)
- Low latency pyramid processor for image processing systems (66 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Computer vision
- Algorithm
His main research concerns Artificial intelligence, Computer vision, Image processing, Iris and Template.
His study in Pyramid, Quarter-pixel motion and Image resolution falls under the purview of Artificial intelligence.
The concepts of his Pyramid study are interwoven with issues in Single frame, Latency and Computer graphics.
The Quarter-pixel motion study combines topics in areas such as Motion field and Feature.
He interconnects Epipolar geometry, Odometer, Feature detection and Orientation in the investigation of issues within Image resolution.
His Iris research incorporates elements of Matching, Iris image and Biometrics.
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.
