The Experts below are selected from a list of 2067 Experts worldwide ranked by ideXlab platform

Christophe Nicolle - One of the best experts on this subject based on the ideXlab platform.

  • ontology for a panoptes building exploiting contextual information and a Smart Camera Network
    Social Work, 2018
    Co-Authors: Roberto Marroquin, Julien Dubois, Christophe Nicolle
    Abstract:

    The contextual information in the built environment is highly heterogeneous, it goes from static information (e.g., information about the building structure) to dynamic information (e.g., user's space-time information, sensors detections and events that occurred). This paper proposes to semantically fuse the building's contextual information with extracted data from a Smart Camera Network by using ontologies and semantic web technologies. The developed ontology allows interoperability between the different contextual data and enables, without human interaction, real-time event detections and system reconfiguration to be performed. The use of semantic knowledge in multi-Camera monitoring systems guarantees the protection of the user's privacy by not sending nor saving any image, just extracting the knowledge from them. This paper presents a new approach to develop an "all-seeing" Smart building, where the global system is the first step to attempt to provide Artificial Intelligence (AI) to a building.

  • wisenet Smart Camera Network interacting with a semantic model phd forum
    Proceedings of the 10th International Conference on Distributed Smart Camera, 2016
    Co-Authors: Roberto Marroquin, Julien Dubois, Christophe Nicolle
    Abstract:

    This paper presents an innovative concept for a distributed system that combines a Smart Camera Network with semantic reasoning. The proposed system is context sensitive and combines the information extracted by the Smart Camera with logic rules and knowledge of what the Camera observes, building information and events that may occurred. The proposed system is a justification for the use of Smart Cameras, and it can improve the classical visual sensor Networks (VSN) and enhance the standard computer vision approach. The main application of our system is Smart building management, where we specifically focus on increasing the services of the building users.

Demetri Terzopoulos - One of the best experts on this subject based on the ideXlab platform.

  • Smart Camera Networks in virtual reality
    Proceedings of the IEEE, 2008
    Co-Authors: Faisal Qureshi, Demetri Terzopoulos
    Abstract:

    This paper presents our research towards Smart Camera Networks capable of carrying out advanced surveillance tasks with little or no human supervision. A unique centerpiece of our work is the combination of computer graphics, artificial life, and computer vision simulation technologies to develop such Networks and experiment with them. Specifically, we demonstrate a Smart Camera Network comprising static and active simulated video surveillance Cameras that provides extensive coverage of a large virtual public space, a train station populated by autonomously self-animating virtual pedestrians. The realistically simulated Network of Smart Cameras performs persistent visual surveillance of individual pedestrians with minimal intervention. Our innovative Camera control strategy naturally addresses Camera aggregation and handoff, is robust against Camera and communication failures, and requires no Camera calibration, detailed world model, or central controller.

  • Smart Camera Networks in Virtual Reality Simulated Smart Cameras track the movement of simulated pedestrians in a simulated train station, allowing development of improved control strategies for Smart Camera Networks.
    2008
    Co-Authors: Faisal Z. Qureshi, Demetri Terzopoulos
    Abstract:

    This paper presents our research towards Smart Camera Networks capable of carrying out advanced surveil- lance tasks with little or no human supervision. A unique centerpiece of our work is the combination of computer graphics, artificial life, and computer vision simulation tech- nologies to develop such Networks and experiment with them. Specifically, we demonstrate a Smart Camera Network com- prising static and active simulated video surveillance Cameras that provides extensive coverage of a large virtual public space, at rain station populated by autonomously self-animating virtual pedestrians. The realistically simulated Network of Smart Cameras performs persistent visual surveillance of individual pedestrians with minimal intervention. Our innova- tive Camera control strategy naturally addresses Camera aggregation and handoff, is robust against Camera and communication failures, and requires no Camera calibration, detailed world model, or central controller.

  • Smart Camera Networks in virtual reality
    International Conference on Distributed Smart Cameras, 2007
    Co-Authors: Faisal Z. Qureshi, Demetri Terzopoulos
    Abstract:

    We present Smart Camera Network research in the context of a unique new synthesis of advanced computer graphics and vision simulation technologies. We design and experiment with simulated Camera Networks within visually and behaviorally realistic virtual environments. Specifically, we demonstrate a Smart Camera Network comprising static and active simulated video surveillance Cameras that provides perceptive coverage of a large virtual public space, a train station populated by autonomously self-animating virtual pedestrians. In the context of human surveillance, we propose a Camera Network control strategy that enables a collection of Smart Cameras to provide perceptive scene coverage and perform persistent surveillance with minimal intervention. Our novel control strategy naturally addresses Camera aggregation and Camera handoff, it does not require Camera calibration, a detailed world model, or a central controller, and it is robust against Camera failures and communication.

Roberto Marroquin - One of the best experts on this subject based on the ideXlab platform.

  • ontology for a panoptes building exploiting contextual information and a Smart Camera Network
    Social Work, 2018
    Co-Authors: Roberto Marroquin, Julien Dubois, Christophe Nicolle
    Abstract:

    The contextual information in the built environment is highly heterogeneous, it goes from static information (e.g., information about the building structure) to dynamic information (e.g., user's space-time information, sensors detections and events that occurred). This paper proposes to semantically fuse the building's contextual information with extracted data from a Smart Camera Network by using ontologies and semantic web technologies. The developed ontology allows interoperability between the different contextual data and enables, without human interaction, real-time event detections and system reconfiguration to be performed. The use of semantic knowledge in multi-Camera monitoring systems guarantees the protection of the user's privacy by not sending nor saving any image, just extracting the knowledge from them. This paper presents a new approach to develop an "all-seeing" Smart building, where the global system is the first step to attempt to provide Artificial Intelligence (AI) to a building.

  • wisenet Smart Camera Network interacting with a semantic model phd forum
    Proceedings of the 10th International Conference on Distributed Smart Camera, 2016
    Co-Authors: Roberto Marroquin, Julien Dubois, Christophe Nicolle
    Abstract:

    This paper presents an innovative concept for a distributed system that combines a Smart Camera Network with semantic reasoning. The proposed system is context sensitive and combines the information extracted by the Smart Camera with logic rules and knowledge of what the Camera observes, building information and events that may occurred. The proposed system is a justification for the use of Smart Cameras, and it can improve the classical visual sensor Networks (VSN) and enhance the standard computer vision approach. The main application of our system is Smart building management, where we specifically focus on increasing the services of the building users.

Julien Dubois - One of the best experts on this subject based on the ideXlab platform.

  • ontology for a panoptes building exploiting contextual information and a Smart Camera Network
    Social Work, 2018
    Co-Authors: Roberto Marroquin, Julien Dubois, Christophe Nicolle
    Abstract:

    The contextual information in the built environment is highly heterogeneous, it goes from static information (e.g., information about the building structure) to dynamic information (e.g., user's space-time information, sensors detections and events that occurred). This paper proposes to semantically fuse the building's contextual information with extracted data from a Smart Camera Network by using ontologies and semantic web technologies. The developed ontology allows interoperability between the different contextual data and enables, without human interaction, real-time event detections and system reconfiguration to be performed. The use of semantic knowledge in multi-Camera monitoring systems guarantees the protection of the user's privacy by not sending nor saving any image, just extracting the knowledge from them. This paper presents a new approach to develop an "all-seeing" Smart building, where the global system is the first step to attempt to provide Artificial Intelligence (AI) to a building.

  • wisenet Smart Camera Network interacting with a semantic model phd forum
    Proceedings of the 10th International Conference on Distributed Smart Camera, 2016
    Co-Authors: Roberto Marroquin, Julien Dubois, Christophe Nicolle
    Abstract:

    This paper presents an innovative concept for a distributed system that combines a Smart Camera Network with semantic reasoning. The proposed system is context sensitive and combines the information extracted by the Smart Camera with logic rules and knowledge of what the Camera observes, building information and events that may occurred. The proposed system is a justification for the use of Smart Cameras, and it can improve the classical visual sensor Networks (VSN) and enhance the standard computer vision approach. The main application of our system is Smart building management, where we specifically focus on increasing the services of the building users.

Faisal Z. Qureshi - One of the best experts on this subject based on the ideXlab platform.

  • Smart Camera Networks in Virtual Reality Simulated Smart Cameras track the movement of simulated pedestrians in a simulated train station, allowing development of improved control strategies for Smart Camera Networks.
    2008
    Co-Authors: Faisal Z. Qureshi, Demetri Terzopoulos
    Abstract:

    This paper presents our research towards Smart Camera Networks capable of carrying out advanced surveil- lance tasks with little or no human supervision. A unique centerpiece of our work is the combination of computer graphics, artificial life, and computer vision simulation tech- nologies to develop such Networks and experiment with them. Specifically, we demonstrate a Smart Camera Network com- prising static and active simulated video surveillance Cameras that provides extensive coverage of a large virtual public space, at rain station populated by autonomously self-animating virtual pedestrians. The realistically simulated Network of Smart Cameras performs persistent visual surveillance of individual pedestrians with minimal intervention. Our innova- tive Camera control strategy naturally addresses Camera aggregation and handoff, is robust against Camera and communication failures, and requires no Camera calibration, detailed world model, or central controller.

  • Smart Camera Networks in virtual reality
    International Conference on Distributed Smart Cameras, 2007
    Co-Authors: Faisal Z. Qureshi, Demetri Terzopoulos
    Abstract:

    We present Smart Camera Network research in the context of a unique new synthesis of advanced computer graphics and vision simulation technologies. We design and experiment with simulated Camera Networks within visually and behaviorally realistic virtual environments. Specifically, we demonstrate a Smart Camera Network comprising static and active simulated video surveillance Cameras that provides perceptive coverage of a large virtual public space, a train station populated by autonomously self-animating virtual pedestrians. In the context of human surveillance, we propose a Camera Network control strategy that enables a collection of Smart Cameras to provide perceptive scene coverage and perform persistent surveillance with minimal intervention. Our novel control strategy naturally addresses Camera aggregation and Camera handoff, it does not require Camera calibration, a detailed world model, or a central controller, and it is robust against Camera failures and communication.