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检索条件"任意字段=5th Sensor Signal Processing for Defence, SSPD 2015"

共 59 条记录，以下是41-50 订阅

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2015 5th National Conference on Computer Vision, Pattern Recognition, Image processing and Graphics, NCVPRIPG 2015

2015 5th National Conference on Computer Vision, Pattern Rec...

引用

5th National Conference on Computer Vision, Pattern Recognition, Image processing and Graphics, NCVPRIPG 2015

ISBN: (纸本)9781467385640

the proceedings contain 93 papers. the topics discussed include: three dimensional reconstruction of cylindrical pellet using stereo vision;pose and illumination invariant face recognition using binocular stereo 3D reconstruction;sparse representation based background subtraction in videos;generic action recognition from egocentric videos;HSGA: a novel acceleration descriptor for human action recognition;a novel approach for image dehazing combining visible-NIR images;depth estimation from single image using defocus and texture cues;stamp and logo detection from document images by finding outliers;offline handwritten signature verification using Zernike moments;singer based classification of song dataset using vocal signature inherent in signal;a low complexity block matching algorithm for fast motion estimation in high efficiency video coding;rank level fusion in multibiometric systems;kernelization of locality preserving discriminant projection;psoriatic plaque segmentation in skin images;real-time implementation of modified adaptive histogram equalization for high dynamic range infrared images in FPGA;real-time hands-free immersive image navigation system using Microsoft Kinect 2.0 and leap motion controller;human face anthropometric measurement using consumer depth camera;and automated conversion of 2D to 3D image using manifold learning.

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Head Motion Classification for Single-Accelerometer Virtual Reality Hardware 5

Head Motion Classification for Single-Accelerometer Virtual ...

引用

5th International Conference on Frontiers of signal processing (ICFSP)

作者： Hachaj, Tomasz Ogiela, Marek R. Pedag Univ Krakow Inst Comp Sci Krakow Poland AGH Univ Sci & Technol Cryptog & Cognit Informat Res Grp Krakow Poland

ISBN: (纸本)9781728152585

Head motions classification applied to virtual reality (VR) systems is still an open problem without a leading pattern recognition solution. In contrary to typical motion capture pattern recognition problem in this case we use only single inertial measurement unit (IMU) sensor. Head motions that we want to recognize in VR systems might be both natural head motions like nodding or shaking head (they might be used while interacting with VR avatars) and also elements of head-based navigation system or interface. the second type of actions is more challenging because it might contains actions that generate motion trajectories that do not appear in real-life, though they have to be possible to execute only by using a head. In this paper we propose a trajectory-based motion features description that is utilized by dynamic time warping (DTW) classificator. the training of the classificator requires using modified dynamic time warping barycenter averaging (DBA) heuristic algorithm which utilizes quaternions to represents rotations. the proposed pattern recognition system together with its evaluation on the set of head motions acquired by VR system is our original contribution. We have evaluated our method on dataset consisted of 8 types of motions performed by two persons (there are 160 motions samples). In leave-one-out evaluation we have obtained very good results: only 10% of one and 15% of another action has been incorrectly classified, while remaining 6 actions classes had been 100% correctly classified. Both dataset and implementation of proposed method can be downloaded, due to this our experiment can be reproduced.

关键词： Head motion analysis signal processing virtual reality glasses dynamic time warping quaternions

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Track-to-track fusion of out-of-sequence tracks

Track-to-track fusion of out-of-sequence tracks

引用

5th International Conference on Information Fusion, FUSION 2002

作者： Challa, Subhash Legg, Jonathan A. Wang, Xuezhi CRC for Sensor Signal and Info. Processing Dept. Electrical and Electronic Eng. University of Melbourne Melbourne VIC Australia Surveillance Systems Division Defence Science and Technology Organisation Edanburgh SA Australia CSSP Melbourne Melbourne VIC Australia

ISBN: (纸本)0972184414

Fusing out-of-sequence information is a problem of growing importance due to an increased reliance on networked sensors embedded in complicated network architectures. the problem of fusing out-of-sequence measurements (OOSM) has received some attention in literature;however, most practical fusion systems, owing to compatibility with legacy sensors and limited communication bandwidth, send track information instead of raw measurements to the fusion node. Delays introduced by the network can result in the reception of out-of-sequence tracks (OOST). this paper considers the problem of fusing out-of-sequence measurements in general, and proposes an optimal Bayesian solution involving a joint probability density of current and past target states, referred to as augmented states. By representing tracks using equivalent measurements, the relationship between OOSM and OOST-based fusion is shown. the special case of Gaussian statistics is also addressed. © 2002 Int. Soc. of Information Fusion.

关键词： Network architecture

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Proceedings of IMTA-5 2015 - 5th International Workshop on Image Mining. theory and Applications, in conjunction with the 10th Internatioanal Joint Conference on Computer Vision, Imaging and Computer Graphics theory and Applications, VISIGRAPP 2015

Proceedings of IMTA-5 2015 - 5th International Workshop on I...

引用

5th International Workshop on Image Mining. theory and Applications, IMTA-5 2015 - In conjunction with the 10th Internatioanal Joint Conference on Computer Vision, Imaging and Computer Graphics theory and Applications, VISIGRAPP 2015

ISBN: (纸本)9789897580949

the proceedings contain 15 papers. the topics discussed include: development of the logic programming approach to the intelligent monitoring of anomalous human behaviour;location of pupil contour by Hough transform of connectivity components;testing an image mining approach to obtain pressure ulcers stage and texture;on image representing in image analysis;a variational method to remove the combination of Poisson and Gaussian noises;PRIAR using a graph segmentation method;virtual immersive environments for underwater archaeological exploration;current trends in mathematical image analysis - a survey;human pose estimation in video via MCMC sampling;signal processing for underwater archaeology;experimenting an embedded-sensor network for early warning of natural risks due to fast failures along railways;selective use of optimal image resolution for depth from multiple motions based on gradient scheme;and blood flow prediction and visualization within the aneurysm of the middle cerebral artery after surgical treatment.

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Singer Based Classification of Song Dataset Using Vocal Signature Inherent in signal 5

Singer Based Classification of Song Dataset Using Vocal Sign...

引用

5th National Conference on Computer Vision, Pattern Recognition, Image processing and Graphics (NCVPRIPG)

作者： Sarkar, Rajib Saha, Sanjoy Kumar Jadavpur Univ Dept Comp Sci & Engn Kolkata India

ISBN: (纸本)9781467385640

Singer based classification of song data is important in the applications like, organized archival and indexing of music data, music retrieval. In a song, singing voice is mixed with accompanying instrument signal. To extract the vocal characteristics of the singer, the effect of non-voiced part is to be minimized. In this work a simple methodology is proposed to remove the non-voiced segments and to reduce the impression of instruments from the voice-dominating signal. To extract the vocal signature, proposed features extract the variation pattern of zero crossing rate and short term energy. In broad sense, the features try to capture the range of pitch and energy over which a singer mostly operates. this is motivated by the way a human being tries to identify a singer. Finally, singer based classification is done using multi-layer perceptron network. Experiment is carried out with artist 20 dataset and 63% classification accuracy is achieved. Comparison with reported works on the same dataset shows that the performance of the proposed simple methodology is better than the majority and very close to others.

关键词： singer identification time domain filtering frequency domain filtering STE and ZCR based feature MFCC

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High Performance Distributed Acoustic sensor Using Cyclic Pulse Coding in a Direct Detection Coherent-OTDR 5

High Performance Distributed Acoustic Sensor Using Cyclic Pu...

引用

5th Asia-Pacific Optical sensors Conference (APOS)

作者： Muanenda, Yonas Oton, Claudio J. Faralli, Stefano Di Pasquale, Fabrizio Scuola Super Sant Anna I-56124 Pisa Italy

ISBN: (纸本)9781628418651

We propose and experimentally demonstrate a Distributed Acoustic sensor exploiting cyclic Simplex coding in a phase-sensitive OTDR on standard single mode fibers based on direct detection. Suitable design of the source and use of cyclic coding is shown to improve the SNR of the coherent back-scattered signal by up to 9 dB, reducing fading due to modulation instability and enabling accurate long-distance measurement of vibrations with minimal post-processing.

关键词： Rayleigh scattering phi-OTDR Fiber optic sensors cyclic coding distributed acoustic sensing

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Ground Moving Target Imaging and Motion Parameter Estimation Using Radon-Second-order WVD transform 5

Ground Moving Target Imaging and Motion Parameter Estimation...

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IEEE 5th Asia-Pacific Conference on Synthetic Aperture Radar (APSAR)

作者： Huang, Penghui Liao, Guisheng Yang, Zhiwei Xia, Xiang-Gen Ma, Jing-Tao Xidian Univ Natl Lab Radar Signal Proc Xian 710071 Shaanxi Peoples R China Univ Delaware Dept Elect & Comp Engn Newark DE 19716 USA

ISBN: (纸本)9781467372978

For a SAR system with a moving target, long synthetic aperture time may greatly improve the SAR imaging quality, whereas defocusing may occur due to the range cell migration (RCM) and Doppler frequency migration (DFM) effects. To address those issues, a key procedure is to perform the accurate motion compensation, and then, the motion parameter estimation becomes essential. In this paper, a novel motion parameter estimation method named Second-order WVD (SoWVD) transform is proposed, which can achieve motion parameter estimation by 2-D Fourier transform (FT) instead of the exhaustive search of the trajectory slope in time-frequency plane by Wigner-Hough transform (WHT). In the sequel, a new SAR imaging method based on a combined Radon-SoWVD transform is developed, which can simultaneously eliminate the RCM and DFM effects without the restriction of Doppler ambiguity. After compensating target motion effect according to the estimated motion parameters, a ground moving target can be finely imaged. Real data processing results are provided to demonstrate the validity of the proposed imaging method.

关键词： Synthetic aperture radar (SAR) ground moving target imaging (GMTIm) Keystone transform second-order WVD transform (SoWVD) Radon-SoWVD tranform

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High-Order CRF based on Product-of-Experts for Unsupervised SAR Image Multiclass Segmentation 5

High-Order CRF based on Product-of-Experts for Unsupervised ...

引用

IEEE 5th Asia-Pacific Conference on Synthetic Aperture Radar (APSAR)

作者： Zhang, Peng Li, Ming An, Lin Jia, Lit Wu, Yan Xidian Univ Natl Lab Radar Signal Proc Xian Peoples R China Xidian Univ Remote Sensing Image Proc & Fus Grp Sch Elect Engn Xian Peoples R China

ISBN: (纸本)9781467372978

Conditional random fields (CRF) model is suitable for image segmentation because this model directly defines the posterior distribution as a Gibbs field and allows one to capture the dependencies of the observed data. However, this model has a limited ability to capture the high-order label dependencies with only the pairwise potential being constructed generally. Moreover, for synthetic aperture radar (SAR) image segmentation, SAR scattering statistics that are essential to SAR image processing are not considered in CRF model. then in this paper, we propose a high-order CRF model based on product-of-experts (POE) for unsupervised SAR image multiclass segmentation, named as HCRF-POE model. HCRF-POE model decomposes the high-order label dependencies into the low-order ones and constructs the high order potential based on POE, thus effectively capturing high-order label dependencies. In addition, to capture SAR data information including the textural features and the scattering statistics, in a more completed manner, HCRF-POE model integrates SAR data information under unsupervised Bayesian framework. the effectiveness of HCRF-POE model is demonstrated by the application to the unsupervised segmentation of the simulated image and the real SAR images.

关键词： Synthetic aperture radar Image segmentation High-order conditional random fields Product-of-experts

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Validation Of Stimulus For EEG signal Based Cognitive Load Analysis 5

Validation Of Stimulus For EEG Signal Based Cognitive Load A...

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5th National Conference on Computer Vision, Pattern Recognition, Image processing and Graphics (NCVPRIPG)

作者： Sinha, Aniruddha Chatterjee, Debatri Saha, Sanjoy Kumar Basu, Anupam Tata Consultancy Serv Ltd Innovat Lab Kolkata India Jadavpur Univ Comp Sci & Engn Kolkata India Indian Inst Technol Comp Sci & Engn Kharagpur W Bengal India

ISBN: (纸本)9781467385640

Cognitive load is defined as the mental workload imparted on brain while doing a task. the amount of cognitive load experienced depends on individual's ability of perception, assimilation and response to a task. Real-time measurement of the level of cognitive load using low cost Electroencephalogram (EEG) signal enables understanding of personal cognitive skills. In this paper, we propose a methodology of selecting a reference task whose bio-markers closely match with a given task while probing different cognitive abilities. the benefit of this approach is to have a limited set of training models for the reference tasks related to various cognitive categories and use the same for a variety of unknown tasks. Experiment is performed for two levels of cognitive load with three different tasks namely Stroop color task, logical reasoning task and usage of on-screen keyboards. the training models of the reference tasks, selected by cluster analysis of low and high cognitive levels are used to evaluate an unknown task. Experimental results indicate that the Stroop is a better reference for On-Screen keyboard test compared to the Logical reasoning test. Support vector machine (SVM) and principal component analysis (PCA) followed by SVM (PCASVM) are used as the classifiers for the testing.

关键词： cognitive load EEG clustering

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MIMO radar performance in clutter: Limitations imposed by bounds on the volume and height distributions for the MIMO radar ambiguity function

MIMO radar performance in clutter: Limitations imposed by bo...

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sensor Array and Multichannel signal processing Workshop

作者： Yuri I. Abramovich Gordon J. Frazer Intelligence Surveillance and Reconnaissance Division ISRD Defence Science and Technology Organisation Edinburgh SA Australia

In multiple-input multiple-output (MIMO) radar, the efficiency of target detection in clutter that is distributed over a certain range bin-Doppler frequency region depends on the sidelobe level of the waveformspsila auto- and cross-ambiguity functions within this region. We introduce the MIMO ambiguity function as the sum of all auto- and cross-ambiguity functions of the K MIMO radar waveforms, with the integral of this function over some range-Doppler region serving as a measure of the orthogonality (separability) of the waveforms within this region of interest. We derive an upper bound on the attainable ldquoclear areardquo for the MIMO ambiguity function, and show that, with respect to the conventional single-waveform ambiguity function, the maximum clear area is K times smaller for the MIMO system.

关键词： MIMO Radar Clutter Radar antennas Arrays Radar clutter Receiving antennas

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