The Experts below are selected from a list of 22386 Experts worldwide ranked by ideXlab platform
Srayan Datta - One of the best experts on this subject based on the ideXlab platform.
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building a scientific concept hierarchy Database schbase
International Joint Conference on Natural Language Processing, 2015Co-Authors: Eytan Adar, Srayan DattaAbstract:Extracted keyphrases can enhance numerous applications ranging from search to tracking the evolution of scientific discourse. We present SCHBASE, a Hierarchical Database of keyphrases extracted from large collections of scientific literature. SCHBASE relies on a tendency of scientists to generate new abbreviations that “extend” existing forms as a form of signaling novelty. We demonstrate how these keyphrases/concepts can be extracted, and their viability as a Database in relation to existing collections. We further show how keyphrases can be placed into a semantically-meaningful “phylogenetic” structure and describe key features of this structure. The complete SCHBASE dataset is available at: http://cond.org/schbase.html.
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ACL (1) - Building a Scientific Concept Hierarchy Database (SCHBase)
Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language, 2015Co-Authors: Eytan Adar, Srayan DattaAbstract:Extracted keyphrases can enhance numerous applications ranging from search to tracking the evolution of scientific discourse. We present SCHBASE, a Hierarchical Database of keyphrases extracted from large collections of scientific literature. SCHBASE relies on a tendency of scientists to generate new abbreviations that “extend” existing forms as a form of signaling novelty. We demonstrate how these keyphrases/concepts can be extracted, and their viability as a Database in relation to existing collections. We further show how keyphrases can be placed into a semantically-meaningful “phylogenetic” structure and describe key features of this structure. The complete SCHBASE dataset is available at: http://cond.org/schbase.html.
Dimitrios Makris - One of the best experts on this subject based on the ideXlab platform.
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Hierarchical Database for a multi-camera surveillance system
Pattern Analysis and Applications, 2004Co-Authors: J Black, Dimitrios Makris, Tim EllisAbstract:This paper presents a framework for event detection and video content analysis for visual surveillance applications. The system is able to coordinate the tracking of objects between multiple camera views, which may be overlapping or non-overlapping. The key novelty of our approach is that we can automatically learn a semantic scene model for a surveillance region, and have defined data models to support the storage of tracking data with different layers of abstraction into a surveillance Database. The surveillance Database provides a mechanism to generate video content summaries of objects detected by the system across the entire surveillance region in terms of the semantic scene model. In addition, the surveillance Database supports spatio-temporal queries, which can be applied for event detection and notification applications.
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a Hierarchical Database for visual surveillance applications
International Conference on Multimedia and Expo, 2004Co-Authors: J Black, Tim Ellis, Dimitrios MakrisAbstract:This paper presents a framework for event detection and video content analysis for visual surveillance applications. The system is able to coordinate the tracking of objects between multiple camera views, which may be overlapping or non-overlapping. The key novelty of our approach is that we can automatically learn a semantic scene model for a surveillance region, and have defined data models to support the storage of different layers of abstraction of tracking data into a surveillance Database. The surveillance Database provides a mechanism to generate video content summaries of objects detected by the system across the entire surveillance region in terms of the semantic scene model. In addition, the surveillance Database supports spatio-temporal queries, which can be applied for event detection and notification applications
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ICME - A Hierarchical Database for visual surveillance applications
2004 IEEE International Conference on Multimedia and Expo (ICME) (IEEE Cat. No.04TH8763), 2004Co-Authors: J Black, Tim Ellis, Dimitrios MakrisAbstract:This paper presents a framework for event detection and video content analysis for visual surveillance applications. The system is able to coordinate the tracking of objects between multiple camera views, which may be overlapping or non-overlapping. The key novelty of our approach is that we can automatically learn a semantic scene model for a surveillance region, and have defined data models to support the storage of different layers of abstraction of tracking data into a surveillance Database. The surveillance Database provides a mechanism to generate video content summaries of objects detected by the system across the entire surveillance region in terms of the semantic scene model. In addition, the surveillance Database supports spatio-temporal queries, which can be applied for event detection and notification applications
Eytan Adar - One of the best experts on this subject based on the ideXlab platform.
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building a scientific concept hierarchy Database schbase
International Joint Conference on Natural Language Processing, 2015Co-Authors: Eytan Adar, Srayan DattaAbstract:Extracted keyphrases can enhance numerous applications ranging from search to tracking the evolution of scientific discourse. We present SCHBASE, a Hierarchical Database of keyphrases extracted from large collections of scientific literature. SCHBASE relies on a tendency of scientists to generate new abbreviations that “extend” existing forms as a form of signaling novelty. We demonstrate how these keyphrases/concepts can be extracted, and their viability as a Database in relation to existing collections. We further show how keyphrases can be placed into a semantically-meaningful “phylogenetic” structure and describe key features of this structure. The complete SCHBASE dataset is available at: http://cond.org/schbase.html.
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ACL (1) - Building a Scientific Concept Hierarchy Database (SCHBase)
Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language, 2015Co-Authors: Eytan Adar, Srayan DattaAbstract:Extracted keyphrases can enhance numerous applications ranging from search to tracking the evolution of scientific discourse. We present SCHBASE, a Hierarchical Database of keyphrases extracted from large collections of scientific literature. SCHBASE relies on a tendency of scientists to generate new abbreviations that “extend” existing forms as a form of signaling novelty. We demonstrate how these keyphrases/concepts can be extracted, and their viability as a Database in relation to existing collections. We further show how keyphrases can be placed into a semantically-meaningful “phylogenetic” structure and describe key features of this structure. The complete SCHBASE dataset is available at: http://cond.org/schbase.html.
J Black - One of the best experts on this subject based on the ideXlab platform.
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Hierarchical Database for a multi-camera surveillance system
Pattern Analysis and Applications, 2004Co-Authors: J Black, Dimitrios Makris, Tim EllisAbstract:This paper presents a framework for event detection and video content analysis for visual surveillance applications. The system is able to coordinate the tracking of objects between multiple camera views, which may be overlapping or non-overlapping. The key novelty of our approach is that we can automatically learn a semantic scene model for a surveillance region, and have defined data models to support the storage of tracking data with different layers of abstraction into a surveillance Database. The surveillance Database provides a mechanism to generate video content summaries of objects detected by the system across the entire surveillance region in terms of the semantic scene model. In addition, the surveillance Database supports spatio-temporal queries, which can be applied for event detection and notification applications.
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a Hierarchical Database for visual surveillance applications
International Conference on Multimedia and Expo, 2004Co-Authors: J Black, Tim Ellis, Dimitrios MakrisAbstract:This paper presents a framework for event detection and video content analysis for visual surveillance applications. The system is able to coordinate the tracking of objects between multiple camera views, which may be overlapping or non-overlapping. The key novelty of our approach is that we can automatically learn a semantic scene model for a surveillance region, and have defined data models to support the storage of different layers of abstraction of tracking data into a surveillance Database. The surveillance Database provides a mechanism to generate video content summaries of objects detected by the system across the entire surveillance region in terms of the semantic scene model. In addition, the surveillance Database supports spatio-temporal queries, which can be applied for event detection and notification applications
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ICME - A Hierarchical Database for visual surveillance applications
2004 IEEE International Conference on Multimedia and Expo (ICME) (IEEE Cat. No.04TH8763), 2004Co-Authors: J Black, Tim Ellis, Dimitrios MakrisAbstract:This paper presents a framework for event detection and video content analysis for visual surveillance applications. The system is able to coordinate the tracking of objects between multiple camera views, which may be overlapping or non-overlapping. The key novelty of our approach is that we can automatically learn a semantic scene model for a surveillance region, and have defined data models to support the storage of different layers of abstraction of tracking data into a surveillance Database. The surveillance Database provides a mechanism to generate video content summaries of objects detected by the system across the entire surveillance region in terms of the semantic scene model. In addition, the surveillance Database supports spatio-temporal queries, which can be applied for event detection and notification applications
Ales Ude - One of the best experts on this subject based on the ideXlab platform.
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ICAR - Cooperative movements through Hierarchical Database search
2017 18th International Conference on Advanced Robotics (ICAR), 2017Co-Authors: Miha Denisa, Bojan Nemec, Ales UdeAbstract:The paper tackles the problem of synthesizing robot movements for human robot collaboration. The proposed approach employs a dual Hierarchical Database, which encodes multiple demonstrated human-robot collaborative movements. The primary Database encodes demonstrated human movements and is enhanced with a directed weighted graph. It is used for human movement recognition. After recognition, the secondary Database, encoding corresponding robot demonstrations, is used to synthesize appropriate collaborative movement. The proposed approach is evaluated through comparison to Interactive Primitives, a popular approach for synthesizing human robot collaborative tasks. Different sets from a Database of two-dimensional human movements are used as example sets for evaluation.
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RAAD - Movement Recognition and Cooperative Task Synthesis Through Hierarchical Database Search
Advances in Intelligent Systems and Computing, 2016Co-Authors: Miha Denisa, Ales UdeAbstract:An approach for movement recognition and cooperative task synthesis is presented. It is based on a two-part Hierarchical Database, one consisting of human motion and the second on cooperative robot movements. While the motion recognition is done through Hierarchical search on the primary part of the Database, the secondary part is used for determining the most probable path for cooperative movement synthesis. Dynamic movement primitives are used to encode the path into a smooth and continuous movement. Initial evaluation, done in simulation, shows the validity of the proposed approach.
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Synthesis of New Dynamic Movement Primitives Through Search in a Hierarchical Database of Example Movements
International Journal of Advanced Robotic Systems, 2015Co-Authors: Miha Denisa, Ales UdeAbstract:This paper presents a novel approach to discovering motor primitives in a Hierarchical Database of example trajectories. An initial set of example trajectories is obtained by human demonstration. The trajectories are clustered and organized in a binary tree-like Hierarchical structure, from which transition graphs at different levels of granularity are constructed. A novel procedure for searching in this Hierarchical structure is presented. It can exploit the interdependencies between movements and can discover new series of partial paths. From these partial paths, complete new movements are generated by encoding them as dynamic movement primitives. In this way, the number of example trajectories that must be acquired with the assistance of a human teacher can be reduced. By combining the results of the Hierarchical search with statistical generalization techniques, a complete representation of new, not directly demonstrated, movement primitives can be generated.
