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IEEE International Conference on image processing

作者： Eleonora D'Arca Ashley Hughes Neil M. Robertson James Hopgood Joint Research Institute for Signal and Image Processing Heriot-Watt University & University of Edinburgh UK

ISBN: (纸本)9781479923427

In this paper we present a novel audio-visual speaker detection and localisation algorithm. Audio source position estimates are computed by a novel stochastic region contraction (SRC) audio search algorithm for accurate speaker localisation. This audio search algorithm is aided by available video information (stochastic region contraction with height estimation (SRC-HE)) which estimates head heights over the whole scene and gives a speed improvement of 56% over SRC. We finally combine audio and video data in a Kalman filter (KF) which fuses person-position likelihoods and tracks the speaker. Our system is composed of a single video camera and 16 microphones. We validate the approach on the problem of video occlusion i.e. two people having a conversation have to be detected and localised at a distance (as in surveillance scenarios vs. enclosed meeting rooms). We show video occlusion can be resolved and speakers can be correctly detected/localised in real data. Moreover, SRC-HE based joint audio-video (AV) speaker tracking outperforms the one based on the original SRC by 16% and 4% in terms of multi object tracking precision (MOTP) and multi object tracking accuracy (MOTA). Speaker change detection improves by 11% over SRC.

关键词： Video Tracking Speaker Tracking Multimodal tracking Optimization methods Sampling Methods Loudspeakers sampling methods Audio Optimization methods SAFETY REVIEW COMMITTEE Video cameras Videotapes CONFERENCE ROOM SEARCHING ALGORITHM video information video data

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Foreword

Proceedings of the 2016 International Conference on Image Pr...

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Proceedings of the 2016 International Conference on image processing, Computer Vision, and Pattern Recognition, IPCV 2016 2016年

作者： Abd-Wahab, Mohd Helmy Al-Bakry, Abbas Al-Holou, Nizar Arabnia, Hamid R. Bhattacharya, Mahua Martinez Castillo, Juan Jose Daimi, Kevin Deligiannidis, Leonidas Djoudi, Lamia Atma Duong, Trung Eshaghian-Wilner, Mary Mehrnoosh Gravvanis, George A. Huang, Ruizhu Jandieri, George Kim, Byung-Gyu Kim, Tai-hoon Korovin, Iakov Lai, Guoming Lee, Hyo Jong Bin Mansor, Muhammad Naufal Marsh, Andrew Mostafaeipour, Ali Park, James J. Patil, Shashikant Ponalagusamy, R. Schaefer, Gerald Singh, Akash Solo, Ashu M.G. Swee, Sim Kok Thomas, Jaya Tinetti, Fernando G. Vladimir, Hahanov Wang, Shiuh-Jeng Yang, Mary Yoe, Hyun You, Jane Zhao, Wenbing Department of Computer Engineering University Tun Hussein Onn Malaysia Malaysia University of IT and Communications Baghdad Iraq Electrical and Computer Engineering Department IEEE/SEM-Computer Chapter University of Detroit Mercy DetroitMI United States University of Georgia United States ABV Indian Institute of Information Technology and Management MHRD Government of India India Acantelys Alan Turing Nikola Tesla Research Group and GIPEB Universidad Nacional Abierta Venezuela Computer Science and Software Engineering Programs Department of Mathematics Computer Science and Software Engineering University of Detroit Mercy DetroitMI United States Department of Computer Information Systems Wentworth Institute of Technology BostonMA United States Synchrone Technologies France Rutgers University State University of New Jersey New Jersey United States University of Southern California California United States Electrical Engineering University of California Los Angeles Los Angeles [UCLA CA United States Advanced Scientific Computing Applied Math and Applications Research Group Applied Mathematics and Numerical Computing and Department of ECE School of Engineering Democritus University of Thrace Xanthi Greece Texas Advanced Computing Center University of Texas AustinTX United States Georgian Technical University Tbilisi Georgia Institute of Cybernetics Georgian Academy of Science Georgia Multimedia Processing CommunicationsLab.[MPCL Department of Computer Science and Engineering College of Engineering SunMoon University Korea Republic of School of Information and Computing Science University of Tasmania Australia Southern Federal University Russia Computer Science and Technology Sun Yat-Sen University Guangzhou China Center for Advanced Image and Information Technology Division of Computer Science and Engineering Chonbuk National University Korea Republic of Faculty of Engineering Technology Kampus Uniciti Alam Universiti Malaysia Perlis UniMAP Malaysi

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Single Cluster PHD SLAM: Application to Autonomous Underwater Vehicles using Stereo Vision

Single Cluster PHD SLAM: Application to Autonomous Underwate...

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Oceans 2013 - Norway

作者： Sharad Nagappa Narcis Palomeras Chee Sing Lee Nuno Gracias Daniel E. Clark Joaquim Salvi Computer Vision and Robotics Group University of Girona Joint Research Institute in Signal and Image Processing Heriot-Watt University

ISBN: (纸本)9781479900022

This paper considers the application of feature-based simultaneous localisation and mapping (SLAM) using a random finite sets (RFS) framework for an autonomous underwater vehicle. SLAM allows for reduction in localisation error by tracking features which provide a fixed external reference. The SLAM problem is addressed here using a single-cluster probability hypothesis density (PHD) filter. The filter uses a particle approximation for the vehicle position with a conditional Gaussian mixture PHD for the feature map. Map features are selected as unique point features generated from a stereo camera on-board the vehicle. We demonstrate the improvement in localisation applying the algorithm to a dataset obtained in an indoor test tank.

关键词： Autonomous underwater vehicles Stereoviews supersonic low altitude missile underwater vehicles Automatic vehicle location Stereo cameras simultaneous localization and mapping

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Parametric distributions for assessing significance in modular partitions of brain networks

Parametric distributions for assessing significance in modul...

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IEEE International Symposium on Biomedical Imaging

作者： Yu-Teng Chang Richard M. Leahy Dimitrios Pantazis McGovern Institute for Brain Research Massachusetts Institute of Technology Cambridge MA USA Signal and Image Processing Institute University of Southern California Los Angeles CA

ISBN: (纸本)9781467364560

Brain networks are often explored with graph theoretical approaches, and community structures identified using modularity-based partitions. Despite the popularity of these methods, the significance of the obtained subnetworks is largely unaddressed in the literature. We present two parametric methods to assess the statistical significance of network partitions, and therefore control against spurious subnetworks that may arise in random graphs, rather than self-organized brain networks. We evaluate these methods with simulated data and resting state fMRI data.

关键词： Eigenvalues and eigenfunctions Mathematical model Monte Carlo methods Communities Testing Vectors Equations

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INTRA-RETINAL LAYER SEGMENTATION OF OPTICAL COHERENCE TOMOGRAPHY USING DIFFUSION MAP

INTRA-RETINAL LAYER SEGMENTATION OF OPTICAL COHERENCE TOMOGR...

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IEEE International Conference on Acoustics, Speech, and signal processing

作者： Raheleh Kafieh Hossein Rabbani Michael Abramoff Milan Sonka Biomedical Engineering Dept. Medical Image & Signal Processing Research Center Isfahan Univ. of Medical Sciences Isfahan Iran The Iowa Institute for Biomedical Imaging The University of Iowa

ISBN: (纸本)9781479903573

Optical coherence tomography (OCT) is known to be one of the powerful and noninvasive methods in retinal imaging. OCT uses retroreflected light to provide micron-resolution, cross-sectional scans of biological tissues. In contrast to OCT technology development, which has been a field of active research since 1991, OCT image segmentation has only been fully explored during the last decade. In this paper, we introduce a fast segmentation method based on a new kind of spectral graph theory named diffusion maps. The research is performed on spectral domain OCT images depicting normal macular appearance. In contrast to our recent methods of graph based OCT image segmentation, the presented approach does not require edge-based image information and rather relies on regional image texture. Consequently, the proposed method demonstrates robustness in situations of low image contrast or poor layer-to-layer image gradients. This method is tested on thirteen 3D macular SD-OCT images obtained from eyes without pathologies with Topcon 3D OCT-1000 imaging system (with a size of 650 × 512 × 128 voxels and a voxel resolution of 4.81 × 13.67 × 24.41 μm~3). The mean unsigned and signed border positioning errors (mean ± SD) was 8.52±3.13 and -4.61±3.35 micrometers, respectively. The average computation time of the proposed algorithms (implemented with MATLAB) was 12 seconds per 2D slice.

关键词： optical coherence tomography Graph theory diffusion image texture image information TISSUES (BIOLOGY) image CONTRAST image segmentation MATLAB computational time pathology

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VESSEL SEGMENTATION IN imageS OF OPTICAL COHERENCE TOMOGRAPHY USING SHADOW INFORMATION AND THICKENING OF RETINAL NERVE FIBER LAYER

VESSEL SEGMENTATION IN IMAGES OF OPTICAL COHERENCE TOMOGRAPH...

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IEEE International Conference on Acoustics, Speech, and signal processing

作者： Raheleh Kafieh Hajar Danesh Hossein Rabbani Michael Abramoff Milan Sonka Biomedical Engineering Dept. Medical Image & Signal Processing Research Center Isfahan Univ. of Medical Sciences Isfahan Iran The Iowa Institute for Biomedical Imaging The University of Iowa

ISBN: (纸本)9781479903573

The correct segmentation of blood vessels in optical coherence tomography (OCT) images is an important requirement for better diagnosis of many retinal diseases. Although OCT blood vessel segmentation is often performed by applying vessel detection methods on 2D projection of OCT datasets, some papers investigate the vessel segmentation on OCT slices. The presence of shadows in outer retinal layers is established as the main factor for vessel localization;however, the shadow information fails to localize many important blood vessels. The proposed method is based on anatomical changes of Retinal Nerve Fiber Layer (RNFL) in presence of vessels. In this paper we find the thickening of RNFL by applying a layer segmentation algorithm on OCT slices and combine this information with shadow localization. Furthermore, a vessel detection method based on curvelet transform is also applied on 2D projection of OCTs to be added to localized vessels from OCTs. The results show that combination of vessel detection on 2D projection with vessel localization on OCTs can improve the accuracy up to 0.96 which is promisingly higher than older methods.

关键词： Vessel segmentation OCT image Retinal Nerve Fiber Layer optical coherence tomography Blood Vessels Thickening pressure vessels images 3-glucosaminoglycan sulfate shadows inspection methods segmentation Segmentation Fiber

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Channel estimation for spatial modulation

Channel estimation for spatial modulation

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IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)

作者： Xiping Wu Marco Di Renzo Harald Haas Institute for Digital Communications Joint Research Institute for Signal and Image Processing School of Engineering The University of Edinburgh EH9 3JL Edinburgh UK Laboratory for Signals and Systems (LSS) École Supérieure d'Électricité (SUPELEC) Gif-sur-Yvette Paris France

In single-stream multiple-input multiple-output (MIMO) schemes, such as spatial modulation (SM) and space shift keying (SSK), a single transmit antenna is activated at any given time. Therefore, unlike multi-stream MIMO transmitters, simultaneous pilot transmissions are prohibitive because of a single radio-frequency (RF) chain. In state-of-the-art literature, the channels of different transmit antennas are individually estimated. As a result, more time is required to transfer pilots and the effective data rate is compromised. In this paper, we propose a novel channel estimation (CE) technique for single-stream MIMO systems. Given a pilot ratio, the proposed scheme achieves the same estimation period as multi-stream MIMO systems without needing any additional information or feedback. Simulations are implemented under a practical base station environment. Results show that for various speeds of the mobile user, the proposed approach significantly improves the performance of SM in comparison to the conventional CE method.

关键词： Channel estimation Transmitting antennas MIMO Receiving antennas Estimation Modulation Indexes

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Fractional Frequency Reuse in Optical Wireless Cellular Networks

Fractional Frequency Reuse in Optical Wireless Cellular Netw...

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IEEE International Symposium on Personal, Indoor and Mobile Radio Communications

作者： Cheng Chen Nikola Serafimovski Harald Haas Institute for Digital Communications Joint Research Institute for Signal and Image Processing The University of Edinburgh EH9 3JL Edinburgh UK

ISBN: (纸本)9781467362337

Interference coordination in optical wireless cellular networks using different frequency reuse techniques are discussed and compared in this paper. On the one hand, full frequency reuse maximises the system throughput at the cost of poor celledge user performance. On the other hand, cluster-based static resource partitioning offers good cell-edge user performance at the cost of low system throughput. Fractional frequency reuse (FFR) is introduced as a compromise between cell-edge user performance and the system throughput with low system complexity. Simulation results show that a guaranteed user throughput of 5.6 Mbps and an average area spectral efficiency (ASE) of 0.3389 bps/Hz/m~2 are achieved by the FFR optical wireless system with appropriate power control factors. These results show considerable throughput improvement compared to both benchmark systems. It is also shown that by adjusting the LED transmission optical power of a system using visible light spectrum, the illumination requirement for an office room can be satisfied without extra lighting facilities.

关键词： optical wireless communications fractional frequency reuse co-channel interference and orthogonal frequency division multiple access

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Exploiting User Movement Patterns to Enhance Energy Efficiency in Wireless Networks

Exploiting User Movement Patterns to Enhance Energy Efficien...

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IEEE International Symposium on Personal, Indoor and Mobile Radio Communications

作者： Stefan Videv John S. Thompson Harald Haas Institute for Digital Communications Joint Research Institute for Signal and Image Processing The University of Edinburgh EH9 3JL Edinburgh UK

ISBN: (纸本)9781467362337

This paper presents an initial study on how to model user mobility in a wireless cellular network scenario. The model provides realistic patterns of movement between a number of locations. The aforementioned mobility model is built upon to introduce a base station (BS) energy efficient power state control algorithm (EESC) that is able to provide significant energy savings for the simulated scenario. Erratic subsequent on and off BS behavior is avoided by referring to an average loading curve, generated for each BS during a learning period, when making decisions. Moreover, BSs are turned off only when the users can be handed off to nearby cells with a predefined maximum allowed predicted loss in data rate. The resulting system is able to deliver an energy consumption reduction between 36% and 11% over an always on benchmark for the simulated scenarios. There is negligible loss in terms of achieved data rate per user.

关键词： Patterns Enhance benchmark

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A Comparison between DCO-OFDMA and Synchronous One-Dimensional OCDMA for Optical Wireless Communications

A Comparison between DCO-OFDMA and Synchronous One-Dimension...

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IEEE International Symposium on Personal, Indoor and Mobile Radio Communications

作者： John Fakidis Dobroslav Tsonev Harald Haas Institute for Digital Communications Joint Research Institute for Signal and Image Processing The University of Edinburgh EH9 3JL Edinburgh UK

ISBN: (纸本)9781467362337

In this paper, a comparison between direct-current-biased optical orthogonal frequency-division multiple-access (DCO-OFDMA) and synchronous one-dimensional (1-D) optical code-division multiple-access (OCDMA) is performed for optical wireless communication (OWC). Line-of-sight (LOS) channel conditions are considered in an indoor downlink scenario. The bit-error ratio (BER) performance is investigated in an additive white Gaussian noise (AWGN) channel under the conditions of equal spectral and power efficiency. For DCO-OFDMA and 1-D OCDMA, the negative-level clipping effect and multiple-access interference (MAI) are considered, respectively. For the OCDMA scheme, the categories of optical orthogonal codes (OOCs) and unipolar Walsh-Hadamard codes (WHCs) are employed. The time-division multiple-access (TDMA) is also represented in the context of synchronous OCDMA by the use of identity matrices. In order to enhance the 1-D OCDMA spectral efficiency, unipolar M-ary pulse amplitude modulation (M-PAM) is employed. The BER performance versus the average electrical signal-to-noise ratio (SNR) per bit is illustrated both for the single and the multiple-user communication using Monte Carlo simulations.

关键词： Comparison between DCO-OFDMA Synchronous One-Dimensional OCDMA Optical Wireless Communications

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