The Experts below are selected from a list of 312 Experts worldwide ranked by ideXlab platform
N. Murtuza - One of the best experts on this subject based on the ideXlab platform.
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Multimodal face recognition: combination of geometry with physiological information
2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05), 2005Co-Authors: I.a. Kakadiaris, G. Passalis, T. Theoharis, G. Toderici, I. Konstantinidis, N. MurtuzaAbstract:It is becoming increasingly important to be able to credential and identify Authorized Personnel at key points of entry. Such identity management systems commonly employ biometric identifiers. In this paper, we present a novel multimodal facial recognition approach that employs data from both visible spectrum and thermal infrared sensors. Data from multiple cameras is used to construct a three-dimensional mesh representing the face and a facial thermal texture map. An annotated face model with explicit two-dimensional parameterization (UV) is then fitted to this data to construct: 1) a three-channel UV deformation image encoding geometry, and 2) a one-channel UV vasculature image encoding facial vasculature. Recognition is accomplished by comparing: 1) the parametric deformation images, 2) the parametric vasculature images, and 3) the visible spectrum texture maps. The novelty of our work lies in the use of deformation images and physiological information as means for comparison. We have performed extensive tests on the Face Recognition Grand Challenge v1.0 dataset and on our own multimodal database with very encouraging results.
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CVPR (2) - Multimodal face recognition: combination of geometry with physiological information
2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05), 2005Co-Authors: I.a. Kakadiaris, G. Passalis, T. Theoharis, G. Toderici, I. Konstantinidis, N. MurtuzaAbstract:It is becoming increasingly important to be able to credential and identify Authorized Personnel at key points of entry. Such identity management systems commonly employ biometric identifiers. In this paper, we present a novel multimodal facial recognition approach that employs data from both visible spectrum and thermal infrared sensors. Data from multiple cameras is used to construct a three-dimensional mesh representing the face and a facial thermal texture map. An annotated face model with explicit two-dimensional parameterization (UV) is then fitted to this data to construct: 1) a three-channel UV deformation image encoding geometry, and 2) a one-channel UV vasculature image encoding facial vasculature. Recognition is accomplished by comparing: 1) the parametric deformation images, 2) the parametric vasculature images, and 3) the visible spectrum texture maps. The novelty of our work lies in the use of deformation images and physiological information as means for comparison. We have performed extensive tests on the Face Recognition Grand Challenge v1.0 dataset and on our own multimodal database with very encouraging results.
Wen Fei Wu - One of the best experts on this subject based on the ideXlab platform.
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Research on Wireless Location Technology of Nuclear Power Plant and Discussion for Physical Protection System Application
Lecture Notes in Electrical Engineering, 2017Co-Authors: Lin Ye, Hua Ping Chen, Shuang Li, Wen Fei WuAbstract:Several kinds of indoor wireless location technology are introduced in this paper, such as the Radio Frequency Identification (RFID), Bluetooth, Light Emitting Diode (LED) visible light location, and Ultra Wideband (UWB), which are analyzed and compared. Moreover, the paper also discusses the nuclear facilities physical protection system application of wireless location technology in nuclear power plant by means of collecting the location information of the internal Authorized Personnel to analyze the internal Authorized Personnel’s behavior furthermore for the analysis of the internal threats with the data. And by using the wireless localization technologies it is expected to manage and control the nuclear materials in the real-time and achieve nuclear materials specified in the security area to prevent nuclear materials from being stolen or illegal transfer.
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Research on wireless location technology of nuclear power plant and discussion for physical protection system application
Lecture Notes in Electrical Engineering, 2017Co-Authors: Lin Ye, Hua Ping Chen, Shuang Li, Wen Fei WuAbstract:© Springer Nature Singapore Pte Ltd. 2017. Several kinds of indoor wireless location technology are introduced in this paper, such as the Radio Frequency Identification (RFID), Bluetooth, Light Emitting Diode (LED) visible light location, and Ultra Wideband (UWB), which are analyzed and compared. Moreover, the paper also discusses the nuclear facilities physical protection system application of wireless location technology in nuclear power plant by means of collecting the location information of the internal Authorized Personnel to analyze the internal Authorized Personnel’s behavior furthermore for the analysis of the internal threats with the data. And by using the wireless localization technologies it is expected to manage and control the nuclear materials in the real-time and achieve nuclear materials specified in the security area to prevent nuclear materials from being stolen or illegal transfer.
Sanja Vrane - One of the best experts on this subject based on the ideXlab platform.
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DEXA Workshops - Smart Indoor Positioning System for Situation Awareness in Emergency Situations
2015 26th International Workshop on Database and Expert Systems Applications (DEXA), 2015Co-Authors: Lazar Berbakov, Bogdan Pavkovic, Sanja VraneAbstract:In this paper, we propose an indoor positioning system for situation awareness in emergency situations. We consider a system that uses inertial sensors to provide positioning information in environments without GNSS coverage. We present the overall system architecture with the special emphasis on a smartphone application for indoor positioning and a mapping web portal where Authorized Personnel is given access to the positioning data.
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Smart Indoor Positioning System for Situation Awareness in Emergency Situations
2015 26th International Workshop on Database and Expert Systems Applications (DEXA), 2015Co-Authors: Lazar Berbakov, Bogdan Pavkovic, Sanja VraneAbstract:In this paper, we propose an indoor positioning system for situation awareness in emergency situations. We consider a system that uses inertial sensors to provide positioning information in environments without GNSS coverage. We present the overall system architecture with the special emphasis on a smartphone application for indoor positioning and a mapping web portal where Authorized Personnel is given access to the positioning data.
I.a. Kakadiaris - One of the best experts on this subject based on the ideXlab platform.
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Multimodal face recognition: combination of geometry with physiological information
2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05), 2005Co-Authors: I.a. Kakadiaris, G. Passalis, T. Theoharis, G. Toderici, I. Konstantinidis, N. MurtuzaAbstract:It is becoming increasingly important to be able to credential and identify Authorized Personnel at key points of entry. Such identity management systems commonly employ biometric identifiers. In this paper, we present a novel multimodal facial recognition approach that employs data from both visible spectrum and thermal infrared sensors. Data from multiple cameras is used to construct a three-dimensional mesh representing the face and a facial thermal texture map. An annotated face model with explicit two-dimensional parameterization (UV) is then fitted to this data to construct: 1) a three-channel UV deformation image encoding geometry, and 2) a one-channel UV vasculature image encoding facial vasculature. Recognition is accomplished by comparing: 1) the parametric deformation images, 2) the parametric vasculature images, and 3) the visible spectrum texture maps. The novelty of our work lies in the use of deformation images and physiological information as means for comparison. We have performed extensive tests on the Face Recognition Grand Challenge v1.0 dataset and on our own multimodal database with very encouraging results.
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CVPR (2) - Multimodal face recognition: combination of geometry with physiological information
2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05), 2005Co-Authors: I.a. Kakadiaris, G. Passalis, T. Theoharis, G. Toderici, I. Konstantinidis, N. MurtuzaAbstract:It is becoming increasingly important to be able to credential and identify Authorized Personnel at key points of entry. Such identity management systems commonly employ biometric identifiers. In this paper, we present a novel multimodal facial recognition approach that employs data from both visible spectrum and thermal infrared sensors. Data from multiple cameras is used to construct a three-dimensional mesh representing the face and a facial thermal texture map. An annotated face model with explicit two-dimensional parameterization (UV) is then fitted to this data to construct: 1) a three-channel UV deformation image encoding geometry, and 2) a one-channel UV vasculature image encoding facial vasculature. Recognition is accomplished by comparing: 1) the parametric deformation images, 2) the parametric vasculature images, and 3) the visible spectrum texture maps. The novelty of our work lies in the use of deformation images and physiological information as means for comparison. We have performed extensive tests on the Face Recognition Grand Challenge v1.0 dataset and on our own multimodal database with very encouraging results.
Minghua Chen - One of the best experts on this subject based on the ideXlab platform.
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ICIP (3) - Hiding privacy information in video surveillance system
IEEE International Conference on Image Processing 2005, 2020Co-Authors: Wei Zhang, Sen-ching S. Cheung, Minghua ChenAbstract:This paper proposes a detailed framework of storing privacy information in surveillance video as a watermark. Authorized Personnel is not only removed from the surveillance video as in J. Wickramasuriya et al. (2004) but also embedded into the video itself, which can only be retrieved with a secrete key. A perceptual-model-based compressed domain video watermarking scheme is proposed to deal with the huge payload problem in the proposed surveillance system. A signature is also embedded into the header of the video as in M. Pramateftakis et al. (2004) for authentication. Simulation results have shown that the proposed algorithm can embed all the privacy information into the video without affecting its visual quality. As a result, the proposed video surveillance system can monitor the unAuthorized persons in a restricted environment, protect the privacy of the Authorized persons but, at the same time, allow the privacy information to be revealed in a secure and reliable way.
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Hiding privacy information in video surveillance system
IEEE International Conference on Image Processing 2005, 2005Co-Authors: Wei Zhang, S.s. Cheung, Minghua ChenAbstract:This paper proposes a detailed framework of storing privacy information in surveillance video as a watermark. Authorized Personnel is not only removed from the surveillance video as in J. Wickramasuriya et al. (2004) but also embedded into the video itself, which can only be retrieved with a secrete key. A perceptual-model-based compressed domain video watermarking scheme is proposed to deal with the huge payload problem in the proposed surveillance system. A signature is also embedded into the header of the video as in M. Pramateftakis et al. (2004) for authentication. Simulation results have shown that the proposed algorithm can embed all the privacy information into the video without affecting its visual quality. As a result, the proposed video surveillance system can monitor the unAuthorized persons in a restricted environment, protect the privacy of the Authorized persons but, at the same time, allow the privacy information to be revealed in a secure and reliable way.
