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Dynamic resource allocation for target tracking in sensor and robot networks

Dynamic resource allocation for target tracking in sensor an...

Conference on Sensors, and Command, Control, Communications, and Intelligence (C31) Technologies for Homeland Security and Homeland Defense IV

作者： Shan, XN Tan, JD Michigan Technol Univ Dept Elect & Comp Engn Houghton MI 49931 USA

ISBN: (纸本)0819457639

Sensor network is generally composed of a set of sensors with limited computation capability and power supply. Thus. a well-defined allocation scheme is essential for maintaining the whole sensor network. This paper investigates the dynamic resource allocation problem in a sensor and robot networks for mobile target tracking tasks. Most of sensors will be in sleep mode except for the ones that can contribute for tracking. The sensor network resource allocation is achieved by a hierarchical structure-clustering. Upon detecting an interested event, a set of sensors form a cluster. Only cluster members will be activated during the tracking task. The cluster headship and membership will be updated based on the target's movement properties. In this paper, the clustering algorithm considers sensing area with communication holes and a routing tree is set up within the cluster. For a cluster with communication and/or sensing holes, mobile sensors will be deployed to enhance the sensing and communication capability in the clustering area. Simulations have been used to verify the proposed algorithm.

关键词： Sensors Sensor networks Head detection and tracking algorithms Target detection Mobile communications Computer simulations Homeland security Signal processing Computer engineering

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Adaptive clutter suppression for ground penetrating radar

Adaptive clutter suppression for ground penetrating radar

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Conference on detection and Remediation Technologies for Mines and Minelike Targets X

作者： Carhoun, DO Engn Technol Inc Orlando FL 32826 USA

ISBN: (纸本)0819457795

Adaptive methods are currently in use for GPR to detect shallow-buried targets in the presence of ground-bounce that may be orders of magnitude greater than the target response. One such method that has been used with noteworthy success to reduce the soil background has been called the Principal Components Algorithm (PCA) that applies the Mahalanobis distance measure, a quadratic form, to distinguish the energy in a target from the background energy. We discuss an alternative vector subspace discrimination method borrowed from adaptive spatial filtering that has been used successfully for suppressing Doppler-spread ionospheric clutter in a high frequency radar application [4,5]. This method first estimates the background vector subspace containing the clutter during a training phase and then projects the current response on the orthogonal complement of the estimated subspace to extract the desired signal during the search phase. Discrete clutter in the output response is reduced without attenuating the target signal by applying constraints derived from the estimated target eigenstructure, either measured or modeled. Mathematical details of the algorithm are presented in an appendix. Comparison of results of the PCA and vector subspace projection methods applied to a stepped-frequency GPR have shown the performance of the proposed algorithm to be better in terms of clutter suppression and principal component economy while also retaining the phase and amplitude of the signal samples to facilitate array processing useful for forward looking ground penetrating radar.

关键词： General packet radio service Principal component analysis Receivers detection and tracking algorithms Target detection Phased arrays Ground penetrating radar Data fusion Land mines Sensors

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Modeling the user preference of broadcasting content using Bayesian networks

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JOURNAL OF ELECTRONIC IMAGING 2005年第2期14卷 023022.1-023022.1页

作者： Kang, S Lim, J Kim, M Informat & Commun Univ Sch Engn Lab Multimedia Comp Commun & Broadcasting Taejon 305714 South Korea

We introduce a novel model capturing user preference using the Bayesian approach for recommending users' preferred multimedia content. Unlike other preference models, our method traces the trend of a user preference in time. It allows us to do online learning so we do not need exhaustive data collection. The tracing of the trend can be done by modifying the frequency of attributes in order to force the old preference to be correlated with the current preference under the assumption that the current preference is correlated with the near future preference. The modification is done by partitioning usage history data into smaller sets in a time axis and then weighting the frequencies of attributes to be computed from the partitioned sets of the usage history data in order to differently reflect their significance on predicting the future preference. In the experimental section, the learning and reasoning on user preference in genres are performed by the proposed method with a set of real TV viewers' watching history data collected from many real households. The reasoning performance by the proposed method is also compared with that by a typical method without training in order to show the superiority of our proposed method. (c) 2005 SPIE and IS&T.

关键词： Machine learning Multimedia Communication engineering Data modeling Error analysis Internet Statistical modeling detection and tracking algorithms Floods Mining

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Wipe scene change detection and classification in video sequences

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JOURNAL OF ELECTRONIC IMAGING 2004年第2期13卷 362-375页

作者： Fernando, WAC Canagarajah, CN Brunel Univ Dept Elect & Comp Engn Uxbridge UB8 3PH Middx England Univ Bristol Image Commun Grp Bristol BS8 1UB Avon England

There is an urgent need to extract key information automatically from video for the purposes of indexing, fast retrieval, and scene analysis. To support this vision, reliable scene change detection algorithms must be developed. This paper describes a novel algorithm for wipe scene change detection in uncompressed and MPEG-1 compressed video sequences using statistical and geometric properties of each image. An efficient algorithm is also proposed to estimate statistical features in compressed video without full frame decompression. From uncompressed and MPEG compressed frames, thumbnails are obtained where pixels are the averages and variances of luminance values of macroblocks. Differences between thumbnails are computed and thresholded, and straight lines are detected in the resulting binary images. Persistence and motion of these lines indicate the presence of a shot transition using wipes. Results on video of various content types are reported and validated with the proposed schemes. Furthermore, results show that the accuracy of the detection is above 95% for uncompressed and above 90% for MPEG-1 compressed video. (C) 2004 SPIE and IST.

关键词： Video Video compression Hough transforms Binary data detection and tracking algorithms Algorithm development Image compression Statistical analysis Feature extraction Cameras

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Projection model snakes for tracking using a Monte Carlo approach

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JOURNAL OF ELECTRONIC IMAGING 2004年第2期13卷 384-398页

作者： Welser, ME Acton, ST Univ Virginia Dept Elect & Comp Engn Virginia Image & Video Anal VIVA Charlottesville VA 22904 USA

We propose a method that uses projection models in conjunction with a sequential Monte Carlo approach to track rigid targets. We specifically address the problems associated with tracking objects in scenarios characterized by cluttered images and high variability In target scale. The projection model snake is introduced in order to track a target boundary over a variety of scales by geometrically transforming the boundary to account for three-dimensional relative motion between the target and camera, The complete solution is a potent synergism of the projection model snake and a sequential Monte Carlo method. The projection model Monte Carlo method randomly generates the parameters of target motion and pose from empirically derived distributions. The resultant "particles" are then weighted according to a likelihood determined by the integration of the mean gradient magnitude around the target contour, yielding the expected target path and pose. We demonstrate the effectiveness of this approach for tracking dynamic targets in sequences with noise, clutter, occlusion, and scale variability. (C) 2004 SPIE and IST.

关键词： Affine motion model Monte Carlo methods detection and tracking algorithms Particles Particle filters Solid modeling 3D modeling Cameras Statistical analysis Motion models

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Low-cost and fast partial decoding of compressed videos

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JOURNAL OF ELECTRONIC IMAGING 2004年第2期13卷 334-340页

作者： Jiang, JM Fang, H Yang, SY Univ Bradford Sch Informat Bradford BD7 1DP W Yorkshire England Chinese Acad Sci Inst Acoust Beijing 100864 Peoples R China

We propose a fast partial decoding algorithm for content access to MPEG compressed videos, where full decompression Is not necessarily required, such as compressed video browsing, content analysis, and specific pattern search. The proposed decoding bypasses the inverse DCT via an approximation process to extract average pixels directly from compressed DCT coefficients, Although such extracted pixels may incur differences compared with their fully decompressed counterparts, extensive experiments show that such partially decoded video frames preserve their content very well and achieve reasonable perceptual quality in terms of visual inspections. (C) 2004 SPIE and IST.

关键词： Video Video compression Image quality Optical inspection Video processing Image compression Image processing detection and tracking algorithms Digital video discs Cell phones

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Low-complexity comprehensive labeling and enhancement algorithm for compound documents

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JOURNAL OF ELECTRONIC IMAGING 2004年第4期13卷 832-859页

作者： Guleryuz, OG DoCoMo Commun Labs USA Inc San Jose CA 95110 USA

We present a multiresolutional algorithm that segments a compound document and uses the results of the segmentation for document enhancement in copier applications. The document is initially segmented into halftone and nonhalftone areas. Based on this segmentation the location of the edges due to text, graphics, and images (and not due to halftone dots) are detected on halftone as well as on nonhalftone portions. We further detect constant-tone regions within nonhalftone areas for subsequent bleed-through removal applications. Edge enhancement on detected edges and de-screening on detected halftones are carried out. The algorithm can detect general halftones over regions of arbitrary sizes and shapes, and it can be straightforwardly adjusted for operation at various dpi resolutions. We obtain high detection probabilities on compound multilingual documents containing halftones and fine text The proposed enhancement stage is tolerant of segmentation errors providing robust performance for the remaining problem cases. Our main contribution is the accomplishment of these tasks with a single pass algorithm that is computationally very simple and that requires less than 1% of full page memory, with active memory requirements less than 0.02% of full page memory. The operation of the algorithm can be imagined as a very thin line (of thickness the size of a "full-stop" in 11 pt text) that rapidly scans an input page while simultaneously producing an output page. (C) 2004 SPIE and IST.

关键词： Halftones Edge detection Image segmentation Linear filtering Printing Scanners detection and tracking algorithms Image filtering Visualization Gaussian filters

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Tuning Retinex parameters

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JOURNAL OF ELECTRONIC IMAGING 2004年第1期13卷 58-64页

作者： Ciurea, F Funt, B Simon Fraser Univ Sch Comp Sci Burnaby BC V5A 1S6 Canada

Our goal is to understand how the Retinex parameters affect the predictions of the model. A simplified Retinex computation is specified in the recent MATLAB(TM) implementation;however, there remain several free parameters that introduce significant variability into the model's predictions. We extend previous work on specifying these parameters. In particular, instead of looking for fixed values for the parameters, we establish methods that automatically determine values for them based on the Input image. These methods are tested on the McCann-McKee-Taylor asymmetric matching data, along with some previously unpublished data that include simultaneous contrast targets. (C) 2004 SPIE and IST.

关键词： Data modeling Data conversion detection and tracking algorithms Error analysis Image processing MATLAB Image compression Image resolution Signal generators Sensors

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A proof of the N-FINDR algorithm for the automated detection of endmembers in a hyperspectral image

A proof of the N-FINDR algorithm for the automated detection...

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Conference onalgorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery X

作者： Winter, ME Univ Hawaii Hawaii Inst Geophys & Planetol Honolulu HI 96822 USA

ISBN: (纸本)081945348X

N-FINDR, an automated end-member detection and unmixing algorithm, was first proposed four years ago. Since then, the algorithm has been used successfully in a number of situations. The apparent success of the N-FINDR algorithm is a strong motivator for a complete review of its approach, from its assumptions to its implementation details. This paper reviews the approach used in N-FINDR, and makes a theoretical argument that the algorithm works. The algorithm can be proven to work perfectly on theoretically perfect data. Moreover, N-FINDR can be shown to have good (although imperfect) convergence properties with non-ideal data.

关键词： Sensors Data modeling Hyperspectral imaging Image sensors algorithms detection and tracking algorithms Algorithm development Minerals Reflectivity Calcite

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An un-cooled thermal array based detector as an advanced security sensor

An un-cooled thermal array based detector as an advanced sec...

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Conference on Sensors and Command, Control, Communications and Intelligence (C31) Technologies for Homeland Security and Homeland Defense III

作者： Dimmer, A IRISYS Towcester NN12 6AD Northants England

ISBN: (纸本)0819453269

A 16x16 un-cooled thermal array based detector (ABD) offers the prospect of a new generation of security sensors, with high false alarm rejection and the ability to detect, track and count the number of intruders. The IRISYS array provides the ability not simply to detect an intruder, but by tracking them as a true moving target discriminate between real and false alarm sources. Target processing is carried out within the sensor allowing the position and size of each target within the field of view to be generated. The location and size for each target is output as a low bandwidth data message suitable for transmission over alarm signalling networks. A central security management system or alarm receiving centre display would provide an operator with an intruder count per room, a pseudo `visual' display of targets and locations, show target vectors on a graphical display and track targets from room to room, allowing an appropriate response to be initiated. Taking the same concepts into external detection, should allow discrimination of humans versus animals or vermin and afford a high level of reasoning to reject environmentally generated false alarms. In external detection applications using the ABD as a trigger for CCTV, intruder location data would be used to steer and zoom a PTZ camera to achieve an identification view. As auto tracking features are added to the latest dome cameras the ABD's ability to track and output simultaneous data from multiple targets will steer a camera between several intruders.

关键词： Sensors Target detection Cameras Detector arrays Computer security Infrared sensors detection and tracking algorithms Homeland security Infrared radiation Thermography

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