James W. Davis mainly investigates Computer vision, Artificial intelligence, Motion estimation, Motion and Motion History Images. His study in the fields of Iterative reconstruction, Segmentation and Object detection under the domain of Computer vision overlaps with other disciplines such as Template. His study in Iterative reconstruction is interdisciplinary in nature, drawing from both Parametrization, Representation, Feature detection and Categorical variable.
In his work, Pixel is strongly intertwined with Pattern recognition, which is a subfield of Artificial intelligence. His studies deal with areas such as Object, Cognitive neuroscience of visual object recognition, Tracking and Cluster analysis as well as Motion estimation. His research investigates the connection with Motion and areas like Gesture recognition which intersect with concerns in Position and Pattern recognition.
James W. Davis mostly deals with Artificial intelligence, Computer vision, Pattern recognition, Motion and Segmentation. He studied Artificial intelligence and Machine learning that intersect with Inference. His Pattern recognition research is multidisciplinary, relying on both Pixel and Prior probability.
As a part of the same scientific study, he usually deals with the Motion, concentrating on Gesture and frequently concerns with Position. His Segmentation research focuses on subjects like Invariant, which are linked to Iterative reconstruction. His Motion field study, which is part of a larger body of work in Motion estimation, is frequently linked to Motion History Images, bridging the gap between disciplines.
His main research concerns Artificial intelligence, Computer vision, Pattern recognition, Set and Prior probability. His work in Artificial intelligence addresses issues such as Machine learning, which are connected to fields such as Motion. James W. Davis regularly ties together related areas like Translation system in his Computer vision studies.
In general Pattern recognition, his work in Segmentation is often linked to Maximum a posteriori estimation linking many areas of study. James W. Davis has researched Prior probability in several fields, including Semantic image segmentation, Support vector machine, Synthetic data and Problem domain. His Pattern recognition study which covers Statistical model that intersects with Visual hull, Markov random field and Classifier.
Artificial intelligence, Computer vision, Pattern recognition, Background subtraction and Secondary hyperparathyroidism are his primary areas of study. By researching both Artificial intelligence and Iterative and incremental development, James W. Davis produces research that crosses academic boundaries. James W. Davis integrates many fields in his works, including Computer vision and Frame.
His Pattern recognition study integrates concerns from other disciplines, such as Covariance matrix, Spectral clustering, Robustness and Biclustering. The Background subtraction study combines topics in areas such as Epipolar geometry, Fundamental matrix, Point tracking and Geometry. His Hyperparathyroidism research is multidisciplinary, incorporating elements of Calcitonin, Renal osteodystrophy and Osteoid.
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The recognition of human movement using temporal templates
A.F. Bobick;J.W. Davis.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2001)
The representation and recognition of human movement using temporal templates
J.W. Davis;A.F. Bobick.
computer vision and pattern recognition (1997)
The KidsRoom: A Perceptually-Based Interactive and Immersive Story Environment
Aaron F. Bobick;Stephen S. Intille;James W. Davis;Freedom Baird.
Teleoperators and Virtual Environments (1999)
Motion segmentation and pose recognition with motion history gradients
G.R. Bradski;J. Davis.
workshop on applications of computer vision (2000)
Real-time closed-world tracking
S.S. Intille;J.W. Davis;A.F. Bobick.
computer vision and pattern recognition (1997)
FGF23 neutralization improves chronic kidney disease–associated hyperparathyroidism yet increases mortality
Victoria Shalhoub;Edward M. Shatzen;Sabrina C. Ward;James Davis.
Journal of Clinical Investigation (2012)
Background-subtraction using contour-based fusion of thermal and visible imagery
James W. Davis;Vinay Sharma.
Computer Vision and Image Understanding (2007)
Visual gesture recognition
J. Davis;M. Shah.
IEE Proceedings - Vision, Image, and Signal Processing (1994)
Real-time recognition of activity using temporal templates
A. Bobick;J. Davis.
workshop on applications of computer vision (1996)
A Two-Stage Template Approach to Person Detection in Thermal Imagery
J.W. Davis;M.A. Keck.
workshop on applications of computer vision (2005)
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