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检索条件"主题词=change detection algorithms"

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Scene change detection using DC coefficients

Scene change detection using DC coefficients

引用

IEEE International Conference on Image Processing

作者： O. Bao Ling Guan School of Electrical & Information Engineering University of Sydney Australia Department of Electrical and Computer Engineering Ryerson University Canada

We propose an algorithm to detect shot transitions in MPEG video data in the compressed domain. The algorithm is based on the conventional solution, where energy histograms of DC (discrete cosine) coefficients are used to calculate the distance between consecutive I/P frames, and the DC coefficients of the P-frames are obtained by frame conversion. We enhance the result by using the ratio between two sliding windows to attenuate the low-pass filtered frame distance, and this results in the amplification of the transitional regions. The advantage of our method is that it achieves high detection rates with low computational complexity. The algorithm is equally applicable in detecting sharp transitions and dissolved transitions.

关键词： Layout Video compression Transform coding Gunshot detection systems change detection algorithms Histograms Discrete cosine transforms Data engineering Power engineering and energy Low pass filters

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change detection in signals using linear regression models

Change detection in signals using linear regression models

引用

IEEE International Symposium on Computer Aided Control System Design (CACSD)

作者： T.D. Popescu Research Institute for Informatics Bucharest Romania

The problem of change detection in signals using linear regression models is addressed. Most of the algorithms presented make use of two AR models: a reference model and a current model updated via a sliding block. changes are detected when a suitable distance between these two models is high. Three distance measures are considered in the paper: cepstral distance, log-likelihood ratio (justified by GLR) and a distance involving the cross-entropy of the two conditional probabilities laws (divergence test). Finally, a change detection algorithm using three models and the evolution of Akaike's information criterion is presented. Some results on the application of the discussed algorithms in seismic signal segmentation are included.

关键词： Signal detection Linear regression Testing Signal processing Acoustic signal detection Delay estimation Informatics change detection algorithms Biomedical measurements Geophysical measurements

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A Novel Framework for Urban change detection Using VHR Satellite Images

A Novel Framework for Urban Change Detection Using VHR Satel...

引用

International Conference on Pattern Recognition

作者： Weiming Li Xiaoming Li Yihong Wu Zhanyi Hu National Laboratory of Pattern Recognition Institute of Automation Chinese Academy and Sciences Beijing China Department of Mathematics Shanxi University Shaanxi China

ISBN: (纸本)0769525210

We present a novel framework for detecting urban changes from a pair of very high resolution (VHR) satellite images such as those taken by satellite Quickbird-II or IKONOS. Image differences due to variations of imaging conditions such as view angle and illumination are distinguished from significant urban changes in the scene. First, we adopt a new image registration method, which makes several useful geometrical constraints available. Then we find changed line segments over time. After that we match scale invariant feature transform (SIFT) points and generate corresponding regions in order to exclude changed line segments due to parallax. We perform shadow detection to exclude changed line segments due to shadow change. Finally we group the remaining changed line segments into clusters, among which the significant ones form the changed regions as output. Our experiments with real Quickbird-II images show that the proposed method can well detect significant urban changes

关键词： Satellites Image segmentation Static VAr compensators Layout change detection algorithms Pattern recognition Lighting Image registration Cities and towns Image analysis

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Scene change detection in MPEG domain

Scene change detection in MPEG domain

引用

IEEE Southwest Symposium on Image Analysis and Interpretation

作者： N. Gamaz X. Huang S. Panchanathan Visual Computing and Communications Laboratory Department of Electrical Engineering University of Ottawa Ottawa ONT Canada

Video is an important and challenging media and requires sophisticated indexing schemes for efficient retrieval from visual databases. Video segmentation is a fundamental step in video indexing and involves detection of scene changes. In this paper, we propose a fast and robust algorithm for detecting video shot boundaries in the MPEG-2 compressed bitstream with minimal decoding.

关键词： Layout Video compression Indexing Information retrieval Visual databases Robustness change detection algorithms Gunshot detection systems Transform coding Decoding

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Energy-efficient quickest change detection in sensor networks

Energy-efficient quickest change detection in sensor network...

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IEEE/SP Workshop on Statistical Signal Processing (SSP)

作者： Taposh Banerjee Venugopal V. Veeravalli Department of Electrical and Computer Engineering Coordinated Science Laboratory University of Illinois Urbana-Champaign USA

We propose a minimax formulation for quickest change detection in sensor networks, where there is a cost associated with taking observations at each sensor. We present two energy efficient algorithms, centralized and distributed, in which on-off observation control is employed and the change is detected under a constraint on the false alarm rate. We show that these algorithms are asymptotically optimal as the false alarm rate goes to zero and have good performance compared to the straightforward approach of fractional sampling in which the observations are selected randomly.

关键词： change detection algorithms Indexes Random variables Bayesian methods Vectors Centralized control Algorithm design and analysis

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Unsupervised change detection model based on hybrid conditional random field for high spatial resolution remote sensing imagery

Unsupervised change detection model based on hybrid conditio...

引用

IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Pengyuan Lv Yanfei Zhong Ji Zhao Liangpei Zhang Collaborative Innovation Center of Geospatial Technology Wuhan University Wuhan China Wuhan University Wuhan Hubei CN

In this paper, an unsupervised change detection model based on hybrid conditional random field model (HCRF) is proposed for high spatial resolution (HSR) remote sensing imagery. Traditional random field based algorithms are mainly based on the analysis of the difference image which ignores the spatial-temporal change information of ground objects which is important in dealing with HSR imagery. Thus in HCRF, a new graph structure is designed to explore the correlation of corresponding ground objects from different times to get a better result. The unary potential is selected as the probabilistic result of change vector analysis (CVA), the pairwise potential is modeled to consider the contextual information of difference image and the similarity between objects from bi-temporal original images is considered using an object term. The proposed method is tested on two HSR data sets (IKONOS and QuickBird) and out performs some state-of-art algorithms.

关键词： Remote sensing Spatial resolution change detection algorithms Algorithm design and analysis Image segmentation Feature extraction Correlation

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Data-Driven Quickest change detection in Markov Models

Data-Driven Quickest Change Detection in Markov Models

引用

International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Qi Zhang Zhongchang Sun Luis C. Herrera Shaofeng Zou University at Buffalo the State University of New York

The problem of quickest change detection in Markov models is studied. A sequence of samples are generated from a Markov model, and at some unknown time, the transition kernel of the Markov model changes. The goal is to detect the change as soon as possible subject to false alarm constraints. The data-driven setting is investigated, where neither the pre-nor the post-change Markov transition kernel is known. A kernel based data-driven algorithm is developed, which applies to general state space and is recursive and computationally efficient. Performance bounds on the average running length and worst-case average detection delay are derived. Numerical results are provided to validate the performance of the proposed algorithm.

关键词： change detection algorithms Computational modeling Hidden Markov models Signal processing algorithms Markov processes Signal processing Numerical models

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change detection in High Spatial Resolution Images Based on Support Vector Machine

Change Detection in High Spatial Resolution Images Based on ...

引用

IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Y. Zhigao Q. Qianqing Z. Qifeng State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing Wuhan University of China Wuhan China Jilin Petroleum Group Geophysical Prospecting Corporation Jilin China

With the tendencies of "3-High" for RS images (high spatial resolution, high spectral resolution and high temporal resolution), more attentions are paid to the information processing technique for high-resolution image data. However, the performances of current high spatial resolution RS change detection methods and systems are not satisfying in both effect and efficiency. A new unified approach is presented that integrates SVM based classifier to change detection (SVMCCD). Combined with the change detection task, a bootstrapping strategy is proposed to solve sample selection problem. Considering the relative simplicity of non-change patterns, one- class SVM based change detection method is also provided.

关键词： Spatial resolution Support vector machines Image resolution Support vector machine classification Remote sensing Pixel detection algorithms change detection algorithms Image registration Polynomials

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Unsupervised change detection in the feature space using kernels

Unsupervised change detection in the feature space using ker...

引用

IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Michele Volpi Devis Tuia Gustavo Camps-Valls Mikhail Kanevski Institute of Geomatics and Analysis of Risk University of Lausanne Switzerland Image Processing Laboratory Universitat de València Spain

In this paper we propose an unsupervised approach to change detection by computing the difference image directly in the feature spaces. The resulting difference kernel, that is a combination of kernels computed on the coregistered and radiometrically matched input images, is used to train a nonlinear partitioning algorithm. In order to apply the kernel k-means, issues related to the initialization and to the tuning of parameters (e.g. the Gaussian RBF bandwidth) are considered. To validate the proposed unsupervised algorithm, two multitemporal VHR remote sensing images are used.

关键词： Kernel Remote sensing Partitioning algorithms Clustering algorithms Algorithm design and analysis change detection algorithms Feature extraction

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COMBINED INTENSITY AND COHERENT change detection FOR SYNTHETIC APERTURE RADAR

COMBINED INTENSITY AND COHERENT CHANGE DETECTION FOR SYNTHET...

引用

IEEE International Conference on Acoustics, Speech and Signal Processing

作者： Miriam Cha Rhonda D. Phillips Patrick J. Wolfe MIT Lincoln Laboratory Lexington Massachusetts 02420 USA University College London London WC1E 6BT UK

ISBN: (纸本)9781479928941

Coherent change detection using paired synthetic aperture radar images is performed using a classical coherence estimator applied under an assumption of complex Gaussian data. The magnitudes of the resulting coherence estimates are plotted as an image and used to gauge changes in the observed scene. In this paper, a two-stage change statistic that combines non-coherent and coherent change detection algorithms is proposed. In the first stage, a non-coherent intensity change detector is applied to test for changes caused by the displacement of a sizable object using the sample variance ratio test. The sample pairs that failed the first stage are used as an input to the second stage. The second stage test uses an alternative coherence estimator that assumes equal population variances, to detect subtle changes such as tire tracks and footprints. We show experimentally that the proposed method not only has a superior change detection performance over the classical coherent change detector, but also over either the non-coherent intensity change detector or the alternative coherent change detector, alone. Experimental results are presented to show the effectiveness and robustness of the proposed algorithm for SAR change detection.

关键词： Synthetic aperture radar noncoherent change detection algorithms detector intensity change coherence Footprints

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