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检索条件"主题词=Change detection algorithms"

共 1589 条记录，以下是151-160 订阅

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A change-detection algorithm based on structure and colour

A change-detection algorithm based on structure and colour

引用

IEEE Conference on Advanced Video and Signal Based Surveillance (AVSS)

作者： L. Di Stefano S. Mattoccia M. Mola Advanced Research Center on Electronic Systems University of Bologna Bologna Italy

The paper proposes a novel change-detection algorithm for automated video surveillance applications. The algorithm is based on the idea of incorporating into the background model a set of simple low-level features capable of capturing effectively "structural" (i.e. robust with respect to illumination variations) information. Thanks to this approach, and unlike most conventional change-detection algorithms, the proposed algorithm is capable of handling correctly still and slow objects as well as of working properly throughout very long time spans. Moreover, the algorithm can naturally interact with the higher-level processing modules found in advanced video-based surveillance systems in order to allow for flexible and intelligent background maintenance.

关键词： change detection algorithms Layout Lighting Robustness Surveillance Image analysis Cameras Image color analysis detection algorithms Pixel

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An Adaptive Cusum Test Based on a Hidden Semi-Markov Model for change detection in Non-invasive Mean Blood Pressure Trend

An Adaptive Cusum Test Based on a Hidden Semi-Markov Model f...

引用

Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： Ping Yang Guy Dumont J Mark Ansermino Department of Electrical and Computer Engineering University of British Columbia Vancouver BC Canada Anesthesiology Pharmacology & Therapeutics Departmen University of British Columbia Vancouver BC Canada

A hidden semi-Markov model is proposed to describe a trend signal for non-invasive mean blood pressure. Based on the model, a Viterbi beam search algorithm working with an adaptive cumulative sum test is proposed to detect change points and recognize change patterns online. Testing results on the simulated signals and clinical signals demonstrate that the algorithm has improved performance over the standard cumulative sum test for change detection, and has the potential to provide a clinically relevant description of trend changes

关键词： Testing Blood pressure Biomedical monitoring Hidden Markov models change detection algorithms Pressure measurement Arteries Pattern recognition Pulse measurements Shape

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Real-time scene change detection on compressed multimedia bitstream based on statistical sequential analysis

Real-time scene change detection on compressed multimedia bi...

引用

IEEE International Conference on Multimedia and Expo (ICME)

作者： D. Lelescu D. Schonfeld University of Illinois Chicago Chicago IL USA

In this paper, a novel one-pass, real-time approach to video scene change detection based on statistical sequential analysis and operating on a compressed multimedia bitstream is proposed. Scene change detection is crucial in that it enables subsequent processing operations on video shots, such as video indexing, semantic representation, or tracking of selected video information. Since video sequences contain both abrupt and gradual scene changes, video segmentation algorithms must be able to detect a large variety of changes. Our approach models video sequences as stochastic processes, with scene changes being reflected by changes in the characteristics (parameters) of the process. We use statistical sequential analysis to provide a unified framework for robust and effective detection of both abrupt and gradual scene changes.

关键词： Layout Video compression Video sequences Stochastic processes Sequential analysis Transform coding Statistical analysis Electronic mail Gunshot detection systems change detection algorithms

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A novel approach to change detection based on a coarse-to-fine strategy

A novel approach to change detection based on a coarse-to-fi...

引用

IEEE International Conference on Image Processing

作者： A. Bevilacqua L. Di Stefano A. Lanza G. Capelli Department of Electronics Computer Science and Systems (DEIS) Advanced Research Centre .Ercole De Castro. (ARCES) University of Bologna Bologna Italy

We present a novel approach to the change detection problem based on a coarse-to-fine strategy. The basic idea consists in assigning to an efficient preliminary coarse-level detection the task to filter out the well known possible false changes (e.g., those due to camera noise and small displacements, or to scene illumination changes). This provides the subsequent fine-level detection with reliable supermasks of the true changed areas in the scene. In this way, the fine-level detection can "focus the attention" on limited parts of the frames, thus yielding remarkable advantages in terms of computational efficiency. Here, just a coarse-level detection algorithm based on background subtraction and on the concept of structure is presented, to stress that any pixel-level algorithm can be used afterwards and benefit in terms of robustness as well as of computational efficiency.

关键词： Cameras Layout Lighting detection algorithms change detection algorithms Event detection Noise robustness Computer science Stress Computer vision

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Spatio-spectral anomalous change detection in hyperspectral imagery

Spatio-spectral anomalous change detection in hyperspectral ...

引用

IEEE Global Conference on Signal and Information Processing (GlobalSIP)

作者： James Theiler Los Alamos National Laboratory Los Alamos NM USA

ISBN: (纸本)9781479902460

Because each pixel of a hyperspectral image contains so much information, many (successful) algorithms treat those pixels as independent samples, despite the evident spatial structure in the imagery. One way to exploit this structure is to incorporate spatial processing into pixel-wise anomalous change detection algorithms. But if this is done in the most straightforward way, a contaminated cross-covariance is produced. A spatial processing framework is proposed that avoids this contamination and enhances the performance of anomalous change detection algorithms in hyperspectral imagery.

关键词： Hyperspectral imaging change detection algorithms Smoothing methods Detectors Laboratories

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Information theoretic multivariate change detection for multisensory information processing in Internet of Things

Information theoretic multivariate change detection for mult...

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

作者： Lev Faivishevsky Intel

ISBN: (纸本)9781479999897

Internet of Things (IoT) is one of the main technological trends in the recent years. It allows machine-to-machine communication over the internet. Almost each device may transmit information from its sensors over the web to enable centralized insights derivation in an appropriate cloud architecture. In this paper we review analytical aspects of the sensory information processing. We emphasize the importance of multisensory approach, in which the joint distribution of all sensors values of a device is used to derive insights out of the stream of sensory data. We introduce a novel information theoretic multivariate change detection method based on k-nearest neighbor (kNN) estimation. The algorithm is designed and implemented to satisfy the requirements of IoT for fast online parallel multisensory information processing. We provide a numerical evidence of the validity of the proposed method on simulated and real world data.

关键词： Cloud computing change detection algorithms Sensor phenomena and characterization Information processing Estimation Internet of things

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Scene change detection based on sequence statistics using structural similarity

Scene change detection based on sequence statistics using st...

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Science and Technology Innovation (IAECST), International Academic Exchange Conference on

作者： Jun Shen Xi Jiang Jinshan Zhong Shimeng Yao School of Mathematics Sichuan University Chengdu China

With the development of the short video, video processing technology is becoming more and more important, among which video scene change detection is an important basic technology. However, due to the inconspicuous feature of scene gradual change, the current algorithm cannot detect it very well. Based on this, we proposed a new scene change detection algorithm. The new algorithm is designed based on the structural similarity (SSIM) algorithm, an index to measure the similarity of two images, and the changing law of structural similarity sequence during scene change. Meantime, we designed a new measurement based on sequence statistics to measure the variation law of SSIM sequences. Experiments show that the algorithm has the characteristics of anti-interference and anti-noise, and it can well solve the above difficulty.

关键词： Technological innovation Fluctuations change detection algorithms Current measurement Feature extraction Indexes detection algorithms

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Singular point detection in fingerprints using quadrant change information

Singular point detection in fingerprints using quadrant chan...

引用

International Conference on Pattern Recognition

作者： K. Kryszczuk A. Drygajlo Swiss Federal Institute of Technology Lausanne Switzerland

Automatic localization of singular points in fingerprints is of critical importance in many algorithms. Existing methods of detecting singular points often require tedious ad-hoc parameter tuning, particularly in the presence of degraded quality fingerprints. In this paper we present an approach towards singular point detection in fingerprints that operates on the quadrant change information and is largely insensitive to the degradation of fingerprint quality

关键词： Fingerprint recognition Degradation change detection algorithms Filtering Image matching Robustness Feature extraction Information retrieval Spatial databases Smoothing methods

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A DCT-Based Video Object Segmentation Algorithm for Rainy Situation Using change detection

A DCT-Based Video Object Segmentation Algorithm for Rainy Si...

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International Conference on Innovative Computing, Information and Control (ICICIC)

作者： Da-Jinn Wang Thou-Ho Chen Hung-Shiuan Liau Tsong-Yi Chen Department of Information Management National Kaohsiung Marine University Kaohsiung Taiwan Department of Electronic Engineering National Kaohsiung University University of Applied Science Kaohsiung Taiwan

This paper proposes a DCT-based moving object extraction algorithm which is focused on rainy condition by change detection method. The DCT technique is used to decrease the rainy effect in order to construct a reliable background model. Then, we use change detection to classify pixels in video frame into the foreground region or background region so as to acquire an initial object mask. Besides, reflection effect can be removed from, initial object mask through edge detection and bounding box match. Finally, a post-processing is used to refine the boundary of moving object by connect component labeling and morphological operation. Experimental results show that the proposed algorithm can provide a satisfactory segmentation result in rainy situations

关键词： Object segmentation change detection algorithms Object detection Discrete cosine transforms Image edge detection Image segmentation Reflection Rain Data mining Visual effects

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SAR IMAGE change detection BASED ON MEAN SHIFT PRE-CLASSIFICATION AND FUZZY C-MEANS

SAR IMAGE CHANGE DETECTION BASED ON MEAN SHIFT PRE-CLASSIFIC...

引用

IEEE International Geoscience and Remote Sensing Symposium

作者： Ronghua Shang Kaize Xie Michael Aggrey Okoth Licheng Jiao Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education Xidian University Xi’an China

In order to reduce the influence of noise and obtain better change detection effect, this paper proposes a method for SAR image change detection based on mean shift pre-classification and fuzzy C-means. First, the original image is pre-classified based on mean shift clustering. As a clustering method with non-parametric density estimation, mean shift can effectively maintain the edge information of the object, and can smooth the pixel intensity of the same type of object to reduce the influence of noise on change detection. Then, the difference map is generated by the log-ratio operator and classified into changed area, uncertain area, and unchanged area. After the adjustment, the pre-classification is performed by mean shift and the difference map is generated. Finally, the improved FCM algorithm is used to classify the difference map to generate change detection result map. The effectiveness of the proposed method is verified by experiments with different contrast algorithms on real SAR image datasets.

关键词： change detection algorithms Radar polarimetry Clustering algorithms Classification algorithms Image edge detection Speckle Linear programming

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