His scientific interests lie mostly in Artificial intelligence, Computer vision, Object detection, Pattern recognition and Segmentation. Artificial intelligence and Line are commonly linked in his work. His work in the fields of Image segmentation, Matching, Cognitive neuroscience of visual object recognition and Video tracking overlaps with other areas such as Graph theory.
Ramakant Nevatia has researched Object detection in several fields, including Motion detection, Tracking, Inference and Scale-space segmentation. His Pattern recognition study integrates concerns from other disciplines, such as Boosting, Silhouette, Edge detection and Kernel. The Segmentation study combines topics in areas such as Markov process, Monte Carlo method, Bayesian probability, Markov chain Monte Carlo and Stereopsis.
Ramakant Nevatia mainly investigates Artificial intelligence, Computer vision, Pattern recognition, Object detection and Segmentation. His work on Machine learning expands to the thematically related Artificial intelligence. In his work, Support vector machine is strongly intertwined with Histogram, which is a subfield of Pattern recognition.
His research investigates the connection between Object detection and topics such as Boosting that intersect with issues in Face detection. His research in Segmentation intersects with topics in Stereopsis, Hidden Markov model and Robustness. He combines subjects such as Pixel, Markov process and Iterative reconstruction with his study of Image segmentation.
His scientific interests lie mostly in Artificial intelligence, Computer vision, Pattern recognition, Object detection and Feature extraction. His Artificial intelligence study often links to related topics such as Machine learning. In the field of Computer vision, his study on Segmentation, Tracking, Object-class detection and Video tracking overlaps with subjects such as Focus.
His work on Unsupervised learning as part of general Pattern recognition study is frequently linked to Frame, bridging the gap between disciplines. His Object detection study combines topics in areas such as Optical flow, Boosting and Face detection. The various areas that Ramakant Nevatia examines in his Feature extraction study include Pixel and Information retrieval.
Ramakant Nevatia focuses on Artificial intelligence, Computer vision, Pattern recognition, Object detection and Discriminative model. Feature extraction, Classifier, Face detection, Boosting and Tracking are the core of his Artificial intelligence study. Ramakant Nevatia works mostly in the field of Feature extraction, limiting it down to topics relating to Histogram and, in certain cases, Statistical classification and Normalization, as a part of the same area of interest.
His study in the field of Segmentation, Object-class detection and Video tracking also crosses realms of Initialization. His Pattern recognition research is multidisciplinary, relying on both Action recognition and Feature. In his study, Markov process, Sampling, Monte Carlo method and Visibility is inextricably linked to Motion detection, which falls within the broad field of Object detection.
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Detection of multiple, partially occluded humans in a single image by Bayesian combination of edgelet part detectors
Bo Wu;R. Nevatia.
international conference on computer vision (2005)
Global data association for multi-object tracking using network flows
Li Zhang;Yuan Li;R. Nevatia.
computer vision and pattern recognition (2008)
Linear feature extraction and description
Ramakant Nevatia;K Ramesh Babu.
Computer Graphics and Image Processing (1980)
Tracking multiple humans in complex situations
Tao Zhao;R. Nevatia.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2004)
Robust Object Tracking by Hierarchical Association of Detection Responses
Chang Huang;Bo Wu;Ramakant Nevatia.
european conference on computer vision (2008)
Description and recognition of curved objects
Ramakant Nevatia;Thomas O. Binford.
Artificial Intelligence (1977)
Segment-Based Stereo Matching*
Gerard G Medioni;Ramakant Nevatia.
Graphical Models /graphical Models and Image Processing /computer Vision, Graphics, and Image Processing (1985)
Event detection and analysis from video streams
G. Medioni;I. Cohen;F. Bremond;S. Hongeng.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2001)
Single View Human Action Recognition using Key Pose Matching and Viterbi Path Searching
Fengjun Lv;R. Nevatia.
computer vision and pattern recognition (2007)
Tracking multiple humans in crowded environment
Tao Zhao;R. Nevatia.
computer vision and pattern recognition (2004)
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