Artificial intelligence, Computer vision, Pattern recognition, Object detection and Algorithm are his primary areas of study. Within one scientific family, Robert T. Collins focuses on topics pertaining to Identification under Artificial intelligence, and may sometimes address concerns connected to Field of view. As part of his studies on Computer vision, Robert T. Collins often connects relevant areas like Flow.
Robert T. Collins interconnects Pixel and Mean-shift in the investigation of issues within Pattern recognition. His Object detection research incorporates themes from Motion analysis, Background subtraction, Videoconferencing, Salience and Aerial video. His work carried out in the field of Algorithm brings together such families of science as Active vision, Lattice and Geospatial analysis.
Robert T. Collins mainly focuses on Artificial intelligence, Computer vision, Pattern recognition, Object detection and Image segmentation. His study in Segmentation, Robustness, Video tracking, Image and Object falls under the purview of Artificial intelligence. His Computer vision study which covers Position that intersects with Camera auto-calibration.
His work deals with themes such as Cognitive neuroscience of visual object recognition, Feature, Contextual image classification, Graphical model and Mean-shift, which intersect with Pattern recognition. His research combines Background subtraction and Object detection. His Algorithm research extends to Image segmentation, which is thematically connected.
His main research concerns Artificial intelligence, Computer vision, Kinematics, Tracking and Deep learning. In his research, Pixel is intimately related to Pattern recognition, which falls under the overarching field of Artificial intelligence. His studies in Computer vision integrate themes in fields like Stability and Pairwise comparison.
His Kinematics study combines topics from a wide range of disciplines, such as Assignment problem, Iterated conditional modes and Approximation algorithm. His study focuses on the intersection of Tracking and fields such as Object with connections in the field of Optimal trajectory, Stochastic optimization and Markov chain Monte Carlo. The Deep learning study combines topics in areas such as Simulation and Dynamics.
His scientific interests lie mostly in Artificial intelligence, Computer vision, Video tracking, Mathematical optimization and Pairwise comparison. His Artificial intelligence study frequently links to other fields, such as Assignment problem. The concepts of his Computer vision study are interwoven with issues in Calibration and Pattern recognition.
Robert T. Collins has researched Pattern recognition in several fields, including Pixel, Likelihood function and Metropolis–Hastings algorithm. His Mathematical optimization study incorporates themes from Object and Markov chain Monte Carlo. Robert T. Collins studied Pairwise comparison and Unary operation that intersect with Leverage, Multiple target and Object detection.
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Online selection of discriminative tracking features
R.T. Collins;Yanxi Liu;M. Leordeanu.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2005)
A System for Video Surveillance and Monitoring
Robert T. Collins;Alan J. Lipton;Takeo Kanade;Hironobu Fujiyoshi.
VSAM Final Report by Robotics Institute of CMU (2000)
Mean-shift blob tracking through scale space
computer vision and pattern recognition (2003)
Algorithms for cooperative multisensor surveillance
R.T. Collins;A.J. Lipton;H. Fujiyoshi;T. Kanade.
Proceedings of the IEEE (2001)
A space-sweep approach to true multi-image matching
computer vision and pattern recognition (1996)
Silhouette-based human identification from body shape and gait
R.T. Collins;R. Gross;Jianbo Shi.
ieee international conference on automatic face and gesture recognition (2002)
Introduction to the special section on video surveillance
R.T. Collins;A.J. Lipton;T. Kanade.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2000)
Three-dimensional scene flow
S. Vedula;S. Baker;P. Rander;R. Collins.
international conference on computer vision (1999)
Electrohydrodynamic tip streaming and emission of charged drops from liquid cones
Robert T. Collins;Jeremy J. Jones;Michael T. Harris;Osman A. Basaran.
Nature Physics (2008)
Vision-Based Analysis of Small Groups in Pedestrian Crowds
Weina Ge;R. T. Collins;R. B. Ruback.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2012)
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