The Experts below are selected from a list of 234 Experts worldwide ranked by ideXlab platform

Vinod Kulathumani - One of the best experts on this subject based on the ideXlab platform.

  • ICDSC - Collaborative acquisition of multi-view face images in real-time using a wireless camera network
    2011 Fifth ACM IEEE International Conference on Distributed Smart Cameras, 2011
    Co-Authors: S. Parupati, Rohith Bakkannagari, S. Sankar, Vinod Kulathumani
    Abstract:

    In order to support real-time face recognition using a wireless camera network, we design a data acquisition service to quickly and reliably acquire face images of human subjects from multiple views and to simultaneously index each acquired image into its corresponding pose. In comparison with detection of frontal faces, the detection of non-frontal faces with unknown pose is a much more challenging problem that involves significant image processing. In this paper, we describe a collaborative approach in which multi-view camera geometry and inter-camera communication is utilized at run time to significantly reduce the required processing time. By doing so, we are able to achieve a high capture rate for both frontal and non-frontal faces and at the same time maintain a high detection accuracy. We implement our face acquisition system on a 1.6 GHz Intel Atom Processor based embedded camera network and show that we can reliably acquire frontal faces at 11 fps and non-frontal faces at 10 fps on images captured at a resolution of 640 × 480 pixels.

  • Collaborative acquisition of multi-view face images in real-time using a wireless camera network
    2011
    Co-Authors: S. Parupati, S. Sankar, R. Bakkanagiri, Vinod Kulathumani
    Abstract:

    Abstract—In order to support real-time face recognition using a wireless camera network, we design a data acquisition service to quickly and reliably acquire face images of human subjects from multiple views and to simultaneously index each acquired image into its corresponding pose. In comparison with detection of frontal faces, the detection of non-frontal faces with unknown pose is a much more challenging problem that involves significant image processing. In this paper, we describe a collaborative approach in which multi-view camera geometry and inter-camera communication is utilized at run time to significantly reduce the required processing time. By doing so, we are able to achieve a high capture rate for both frontal and non-frontal faces and at the same time maintain a high detection accuracy. We implement our face acquisition system on a 1.6 GHz Intel Atom Processor based embedded camera network and show that we can reliably acquire frontal faces at 11 fps and non-frontal faces at 10 fps on images captured at a resolution of 640 by 480 pixels. I

S. Parupati - One of the best experts on this subject based on the ideXlab platform.

  • ICDSC - Collaborative acquisition of multi-view face images in real-time using a wireless camera network
    2011 Fifth ACM IEEE International Conference on Distributed Smart Cameras, 2011
    Co-Authors: S. Parupati, Rohith Bakkannagari, S. Sankar, Vinod Kulathumani
    Abstract:

    In order to support real-time face recognition using a wireless camera network, we design a data acquisition service to quickly and reliably acquire face images of human subjects from multiple views and to simultaneously index each acquired image into its corresponding pose. In comparison with detection of frontal faces, the detection of non-frontal faces with unknown pose is a much more challenging problem that involves significant image processing. In this paper, we describe a collaborative approach in which multi-view camera geometry and inter-camera communication is utilized at run time to significantly reduce the required processing time. By doing so, we are able to achieve a high capture rate for both frontal and non-frontal faces and at the same time maintain a high detection accuracy. We implement our face acquisition system on a 1.6 GHz Intel Atom Processor based embedded camera network and show that we can reliably acquire frontal faces at 11 fps and non-frontal faces at 10 fps on images captured at a resolution of 640 × 480 pixels.

  • Collaborative acquisition of multi-view face images in real-time using a wireless camera network
    2011
    Co-Authors: S. Parupati, S. Sankar, R. Bakkanagiri, Vinod Kulathumani
    Abstract:

    Abstract—In order to support real-time face recognition using a wireless camera network, we design a data acquisition service to quickly and reliably acquire face images of human subjects from multiple views and to simultaneously index each acquired image into its corresponding pose. In comparison with detection of frontal faces, the detection of non-frontal faces with unknown pose is a much more challenging problem that involves significant image processing. In this paper, we describe a collaborative approach in which multi-view camera geometry and inter-camera communication is utilized at run time to significantly reduce the required processing time. By doing so, we are able to achieve a high capture rate for both frontal and non-frontal faces and at the same time maintain a high detection accuracy. We implement our face acquisition system on a 1.6 GHz Intel Atom Processor based embedded camera network and show that we can reliably acquire frontal faces at 11 fps and non-frontal faces at 10 fps on images captured at a resolution of 640 by 480 pixels. I

Ioannis Papaefstathiou - One of the best experts on this subject based on the ideXlab platform.

  • WCNC - Fast and power-efficient hardware implementation of a routing scheme for WSNs
    2012 IEEE Wireless Communications and Networking Conference (WCNC), 2012
    Co-Authors: G-g Mplemenos, Ioannis Papaefstathiou
    Abstract:

    One of the most rapidly expanding areas, nowadays, in networking systems is the Wireless Sensor Network (WSN). Typically WSNs rely on multi-hop routing protocols which must be able to establish communication among nodes and guarantee packet deliveries. In this paper, we present a novel approach for the implementation of the WSN routing protocols, which takes advantage of modern FPGAs in order to provide faster routing decisions while consuming significantly less energy than existing systems. Despite our focus on a particular routing protocol (GPSR), the platform developed has the additional advantage that due to the reconfigurability feature of the FPGA it can efficiently execute different routing protocols based on the requirements of the different WSN applications. As our real world experiments demonstrate, we accelerated the execution of the most widely used WSN routing protocol (GPSR) by at least 31 times when compared to the speed achieved when the exact same protocol is executed on a low power Intel Atom Processor. More importantly by utilizing a high-end FPGA the overall energy consumption was reduced by more than 90%.

S. Sankar - One of the best experts on this subject based on the ideXlab platform.

  • ICDSC - Collaborative acquisition of multi-view face images in real-time using a wireless camera network
    2011 Fifth ACM IEEE International Conference on Distributed Smart Cameras, 2011
    Co-Authors: S. Parupati, Rohith Bakkannagari, S. Sankar, Vinod Kulathumani
    Abstract:

    In order to support real-time face recognition using a wireless camera network, we design a data acquisition service to quickly and reliably acquire face images of human subjects from multiple views and to simultaneously index each acquired image into its corresponding pose. In comparison with detection of frontal faces, the detection of non-frontal faces with unknown pose is a much more challenging problem that involves significant image processing. In this paper, we describe a collaborative approach in which multi-view camera geometry and inter-camera communication is utilized at run time to significantly reduce the required processing time. By doing so, we are able to achieve a high capture rate for both frontal and non-frontal faces and at the same time maintain a high detection accuracy. We implement our face acquisition system on a 1.6 GHz Intel Atom Processor based embedded camera network and show that we can reliably acquire frontal faces at 11 fps and non-frontal faces at 10 fps on images captured at a resolution of 640 × 480 pixels.

  • Collaborative acquisition of multi-view face images in real-time using a wireless camera network
    2011
    Co-Authors: S. Parupati, S. Sankar, R. Bakkanagiri, Vinod Kulathumani
    Abstract:

    Abstract—In order to support real-time face recognition using a wireless camera network, we design a data acquisition service to quickly and reliably acquire face images of human subjects from multiple views and to simultaneously index each acquired image into its corresponding pose. In comparison with detection of frontal faces, the detection of non-frontal faces with unknown pose is a much more challenging problem that involves significant image processing. In this paper, we describe a collaborative approach in which multi-view camera geometry and inter-camera communication is utilized at run time to significantly reduce the required processing time. By doing so, we are able to achieve a high capture rate for both frontal and non-frontal faces and at the same time maintain a high detection accuracy. We implement our face acquisition system on a 1.6 GHz Intel Atom Processor based embedded camera network and show that we can reliably acquire frontal faces at 11 fps and non-frontal faces at 10 fps on images captured at a resolution of 640 by 480 pixels. I

G-g Mplemenos - One of the best experts on this subject based on the ideXlab platform.

  • WCNC - Fast and power-efficient hardware implementation of a routing scheme for WSNs
    2012 IEEE Wireless Communications and Networking Conference (WCNC), 2012
    Co-Authors: G-g Mplemenos, Ioannis Papaefstathiou
    Abstract:

    One of the most rapidly expanding areas, nowadays, in networking systems is the Wireless Sensor Network (WSN). Typically WSNs rely on multi-hop routing protocols which must be able to establish communication among nodes and guarantee packet deliveries. In this paper, we present a novel approach for the implementation of the WSN routing protocols, which takes advantage of modern FPGAs in order to provide faster routing decisions while consuming significantly less energy than existing systems. Despite our focus on a particular routing protocol (GPSR), the platform developed has the additional advantage that due to the reconfigurability feature of the FPGA it can efficiently execute different routing protocols based on the requirements of the different WSN applications. As our real world experiments demonstrate, we accelerated the execution of the most widely used WSN routing protocol (GPSR) by at least 31 times when compared to the speed achieved when the exact same protocol is executed on a low power Intel Atom Processor. More importantly by utilizing a high-end FPGA the overall energy consumption was reduced by more than 90%.