His primary areas of investigation include Artificial intelligence, Computer vision, Computer graphics, Pose and 3D reconstruction. His study on Artificial intelligence is mostly dedicated to connecting different topics, such as Pattern recognition. His Histogram, Cognitive neuroscience of visual object recognition and Object detection study in the realm of Computer vision interacts with subjects such as Viola–Jones object detection framework and Object-class detection.
His study in Computer graphics is interdisciplinary in nature, drawing from both Normalization, Field of view, Image and Virtual reality. His research in Pose tackles topics such as Stereo camera which are related to areas like Point cloud. The 3D reconstruction study combines topics in areas such as Stereopsis, Open source, Perceptual user interfaces and Pattern recognition.
Gary Bradski mainly investigates Artificial intelligence, Computer vision, Object, Pattern recognition and Computer graphics. His study in the field of Artificial neural network, Robot and Feature is also linked to topics like Set and Geography. His is involved in several facets of Computer vision study, as is seen by his studies on Pose, Cognitive neuroscience of visual object recognition, Histogram, Object detection and 3D reconstruction.
As part of one scientific family, Gary Bradski deals mainly with the area of Object, narrowing it down to issues related to the Robot manipulator, and often Virtual machine. His studies deal with areas such as Machine learning and Data mining as well as Pattern recognition. The concepts of his Computer graphics study are interwoven with issues in Stereopsis, Field of view and Pattern recognition.
His main research concerns Artificial intelligence, Computer vision, Artificial neural network, Set and Robot manipulator. His work on Iris recognition, Pattern recognition and 3D reconstruction as part of general Artificial intelligence study is frequently connected to Network architecture and Field, therefore bridging the gap between diverse disciplines of science and establishing a new relationship between them. His Computer vision research is mostly focused on the topic Periocular Region.
Gary Bradski combines subjects such as Classifier, Pattern recognition, Biometrics and Data mining with his study of Artificial neural network. His Robot manipulator research integrates issues from Object and Robotic paradigms. The various areas that Gary Bradski examines in his Computer graphics study include Augmented reality, Normalization, Image, Field of view and Virtual reality.
Gary Bradski mainly focuses on Artificial intelligence, Computer vision, Computer graphics, Virtual reality and Field of view. His Computer vision and Pickup and 3D reconstruction investigations all form part of his Computer vision research activities. His Pickup research includes elements of Object, Motion and Robot manipulator.
Gary Bradski integrates Object with Point in his research. His work carried out in the field of 3D reconstruction brings together such families of science as Stereopsis, Open source, Shape matching and Pattern recognition. His research in Virtual reality intersects with topics in Normalization, Augmented reality and Image.
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ORB: An efficient alternative to SIFT or SURF
Ethan Rublee;Vincent Rabaud;Kurt Konolige;Gary Bradski.
international conference on computer vision (2011)
Computer Vision Face Tracking For Use in a Perceptual User Interface
Gary R. Bradski.
Stanley: The Robot that Won the DARPA Grand Challenge
Sebastian Thrun;Michael Montemerlo;Hendrik Dahlkamp;David Stavens.
Journal of Field Robotics (2006)
Map-Reduce for Machine Learning on Multicore
Cheng-tao Chu;Sang K. Kim;Yi-an Lin;Yuanyuan Yu.
neural information processing systems (2006)
Evaluating MapReduce for Multi-core and Multiprocessor Systems
C. Ranger;R. Raghuraman;A. Penmetsa;G. Bradski.
high-performance computer architecture (2007)
Learning OpenCV 3: Computer Vision in C++ with the OpenCV Library
Adrian Kaehler;Gary Bradski.
Fast 3D recognition and pose using the Viewpoint Feature Histogram
Radu Bogdan Rusu;Gary Bradski;Romain Thibaux;John Hsu.
intelligent robots and systems (2010)
Methods and systems for creating virtual and augmented reality
Gary R. Bradski;Samuel A. Miller;Rony Abovitz.
Real time face and object tracking as a component of a perceptual user interface
workshop on applications of computer vision (1998)
Virtual and augmented reality systems and methods
Gary R. Bradski;Brian Schowengerdt;Samuel A. Miller.
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