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Learning speaker, addressee and overlap detection models from multimodal streams 12

Learning speaker, addressee and overlap detection models fro...

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Proceedings of the 14th ACM international conference on Multimodal interaction

作者： Oriol Vinyals Dan Bohus Rich Caruana University of California at Berkeley Berkeley CA USA Microsoft Corporation Redmond WA USA

ISBN: (纸本)9781450314671

A key challenge in developing conversational systems is fusing streams of information provided by different sensors to make inferences about the behaviors and goals of people. Such systems can leverage visual and audio information collected through cameras and microphone arrays, including the location of various people, their focus of attention, body pose, the sound source direction, prosody, and speech recognition results. In this paper, we explore discriminative learning techniques for making accurate inferences on the problems of speaker, addressee and overlap detection in multiparty human-computer dialog. the focus is on finding ways to leverage within- and across-signal temporal patterns and to automatically construct representations from the raw streams that are informative for the inference problem. We present a novel extension to traditional decision trees which allows them to incorporate and model temporal signals. We contrast these methods with more traditional approaches where a human expert manually engineers relevant temporal features. the proposed approach performs well even with relatively small amounts of training data, which is of practical importance as designing features that are task dependent is time consuming and not always possible.

关键词： multiparty turn taking speaker identification multimodal systems random forests addressee detection overlap detection learning with multimodal temporally streaming data multimodal inference

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Impulsive data Association with an Unknown Number of targets

Impulsive Data Association with an Unknown Number of Targets

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14th ACM International conference on Hybrid Systems: Computation and Control

作者： Travers, Matthew Murphey, Todd Pao, Lucy Northwestern Univ Dept Mech Engn Evanston IL 60208 USA

ISBN: (纸本)9781450306294

First- and second-order solution methods for the multi-target data association problem with an unknown number of targets are presented. It is shown that by considering a single continuous measurement signal with impulsive switching between measuring the position of different objects, the data association problem can be recast as a continuous optimization over the impulse times and magnitudes. First- and second-order adjoint formulations are derived which reduce the calculation of the either the first- or second-order derivative of the cost function to a single integration (over any number of impulse times and magnitudes). these adjoint formulations as well as a method for estimating the total number of impulses which occur are the main contributions of this work.

关键词： data Association Optimization Filtering theory

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GMTI tracking in the presence of doppler and range ambiguities

GMTI tracking in the presence of doppler and range ambiguiti...

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作者： Mertens, Michael Nickel, Ulrich Dept. Sensor Data and Information Fusion Fraunhofer FKIE Wachtberg Germany

ISBN: (纸本)9781457702679

this study focuses on tracking targets by airborne ground moving target indication (GMTI) radar in a medium pulse repetition frequency (MPRF) mode, in which both Doppler as well as range ambiguities occur. the standard radar operation is to resolve these ambiguities at the signal processing level by using several PRF. this approach, however, consumes radar energy because multiple bursts are emitted. In this paper, we consider the resolution of the ambiguities at the tracking level based on the assumption that the radar system is operating at a single PRF only. thus, a significant reduction in power consumption is obtained which is crucial for multifunction radar systems. In this work, a Bayesian tracking algorithm is presented which is capable of handling the ambiguities and the related multiple blind zones, the latter being the major challenge for tracking ground moving targets. the performance of the developed algorithm is evaluated based on simulated single target scenarios. © 2011 IEEE.

关键词： Target tracking

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94-GHz Tarsier radar measurements of wind waves and small targets

94-GHz Tarsier radar measurements of wind waves and small ta...

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8th European Radar conference, EuRAD 2011, Held as Part of the 14th European Microwave Week 2011, EuMW 2011

作者： Leonard, Tom Lamont-Smith, Tim Hodges, Robert Beasley, Patrick QinetiQ Malvern St Andrews Road Worcestershire United Kingdom

ISBN: (纸本)9782874870217

Tarsier is QinetiQ's 94-GHz frequency-modulated continuous-wave radar and is installed at several airports worldwide for detecting Foreign Object Debris on runways. the radar is coherent and has a range resolution of 0.3 metres. the sensitivity of the radar that allows it to detect an object the size of a metal bolt at a range of 2 km on land means that in the maritime environment it may detect difficult maritime targets such as swimmers, jetskis, windsurfers, canoes and disturbances of the water surface. this paper describes trials of the Tarsier radar at Cheddar reservoir near Axbridge in Somerset. Non-coherent and coherent radar measurements of wind waves were recorded to characterize the background clutter. targets of opportunity included buoys, wildfowl, windsurfers, rowing boats and a model yacht. A standard 9.4-GHz marine navigation radar was operated at the same time and location to allow a direct comparison of clutter and target signatures at the two different radio frequencies. Results are presented for 94-GHz clutter histograms and Doppler spectra as a function of radar look direction and wind speed. Target signal-to-clutter ratios are discussed for 94 GHz and for 9.4 GHz. It is concluded that Tarsier has the potential to detect short-range maritime threats at this relatively unexplored radio frequency. © 2011 European Microwave Assoc.

关键词： Radar measurement

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Sparsity-aware Kalman tracking of target signal strengths on a grid

Sparsity-aware Kalman tracking of target signal strengths on...

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作者： Farahmand, Shahrokh Giannakis, Georgios B. Leus, Geert Tian, Zhi Dept. of ECE University of Minnesota Minneapolis MN United States Faculty of EE-M-CS Delft Univ. of Technology Delft Netherlands Dept. of ECE Michigan Tech. University Houghton MI United States

ISBN: (纸本)9781457702679

Tracking multiple moving targets is known to be challenged by the nonlinearity present in the measurement equation, and by the computationally burdensome data association task. this paper introduces a grid-based model of target signal strengths leading to linear state and measurement equations, that can afford state estimation via sparsity-aware Kalman filtering (KF), and bypasses data association. Leveraging the sparsity inherent to the novel grid-based model, a sparsity-cognizant KF tracker is developed that effects sparsity through 1-norm regularization. the proposed tracker does not require knowledge of the number of targets or their signal strengths, and exhibits considerably lower complexity than the hidden Markov filter benchmark, especially as the number of targets increases. Numerical simulations demonstrate that the sparsity-cognizant tracker enjoys improved root mean-square error performance at reduced complexity when compared to its sparsity-agnostic counterparts. © 2011 IEEE.

关键词： Kalman filters

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Adaptive air-to-air target tracking in severe jamming environment

Adaptive air-to-air target tracking in severe jamming enviro...

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作者： Feldmann, Michael Nickel, Ulrich Koch, Wolfgang Sensor Data and Information Fusion Dept. Fraunhofer FKIE Neuenahrer Str. 20 53343 Wachtberg Germany

ISBN: (纸本)9781457702679

In the presence of jamming, the task of tracking targets using adaptive phased array radars raises challenges for both signal processing and tracking algorithms. While algorithms for deep nulling of jammers, such as adaptive beamforming, are well-known, tracking algorithms still have to face the problem of the jammer notch, where targets are barely visible (for the antenna) due to jamming interference and/or adaptive jammer suppression. On top of that, tracking algorithms have to cope with inaccurate predictions and large bias of measurements, possibly leading to track instabilities culminating in track loss. this paper deals with the problem of maintaining a track for a single target in severe jamming environment. We present different stabilization measures to improve track stability and track continuity (e.g., avoidance of antenna look directions in the jammer notch, usage of pseudo-measurements to maintain the track file if the predicted target direction is in the jammer notch, etc.). In this context, the most accurate modeling of angle measurement uncertainties plays a decisive role. Simulation results demonstrate significant improvements of tracking performance. © 2011 IEEE.

关键词： Target tracking

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GMTI tracking in the presence of Doppler and range ambiguities

GMTI tracking in the presence of Doppler and range ambiguiti...

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International conference on Information Fusion

作者： Michael Mertens Ulrich Nickel Department Sensor Data and Information Fusion Fraunhofer FKIE Wachtberg Germany

ISBN: (纸本)9781457702679

关键词： Doppler effect Target tracking Roads Radar tracking Doppler radar signal processing algorithms

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Eigenspace analysis for threat detection in social networks

Eigenspace analysis for threat detection in social networks

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作者： Miller, Benjamin A. Beard, Michelle S. Bliss, Nadya T. Lincoln Laboratory Massachusetts Institute of Technology Lexington MA 02420 United States

ISBN: (纸本)9781457702679

the problem of detecting a small, anomalous subgraph within a large background network is important and applicable to many fields. the non-Euclidean nature of graph data, however, complicates the application of classical detection theory in this context. A recent statistical framework for anomalous subgraph detection uses spectral properties of a graph's modularity matrix to determine the presence of an anomaly. In this paper, this detection framework and the related algorithms are applied to data focused on a specific application: detection of a threat subgraph embedded in a social network. the results presented use data created to simulate threat activity among noisy interactions. the detectability of the threat subgraph and its separability from the noise is analyzed under a variety of background conditions in both static and dynamic scenarios. © 2011 IEEE.

关键词： signal detection

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Sparsity-aware Kalman tracking of target signal strengths on a grid

Sparsity-aware Kalman tracking of target signal strengths on...

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International conference on Information Fusion

作者： Shahrokh Farahmand Georgios B. Giannakis Geert Leus Zhi Tian Department of ECE University of Minnesota Minneapolis MN USA Faculty of EE-M-CS Delft University of Technnology Delft Netherlands Department of ECE Michigan Tech University Houghton MI USA

ISBN: (纸本)9781457702679

Tracking multiple moving targets is known to be challenged by the nonlinearity present in the measurement equation, and by the computationally burdensome data association task. this paper introduces a grid-based model of target signal strengths leading to linear state and measurement equations, that can afford state estimation via sparsity-aware Kalman filtering (KF), and bypasses data association. Leveraging the sparsity inherent to the novel grid-based model, a sparsity-cognizant KF tracker is developed that effects sparsity through ℓ 1 -norm regularization. the proposed tracker does not require knowledge of the number of targets or their signal strengths, and exhibits considerably lower complexity than the hidden Markov filter benchmark, especially as the number of targets increases. Numerical simulations demonstrate that the sparsity-cognizant tracker enjoys improved root mean-square error performance at reduced complexity when compared to its sparsity-agnostic counterparts.

关键词： Target tracking Radar tracking Hidden Markov models Sensors Mathematical model Complexity theory Kalman filters

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Adaptive air-to-air target tracking in severe jamming environment

Adaptive air-to-air target tracking in severe jamming enviro...

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International conference on Information Fusion

作者： Michael Feldmann Ulrich Nickel Wolfgang Koch Sensor Data and Information Fusion Department Fraunhofer FKIE Wachtberg Germany

ISBN: (纸本)9781457702679

关键词： Target tracking Jamming Radar tracking Antenna measurements Mathematical model Directive antennas Predictive models

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