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background modeling methods in video analysis： A review and comparative evaluation

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CAAI Transactions on Intelligence Technology 2016年第1期1卷 43-60页

作者： Yong Xu Jixiang Dong Bob Zhang Daoyun Xu Bio-Computing Research Center Shenzhen Graduate School Harbin Institute of Technology 518055 Shenzhen China Shenzhen Key Laboratory of Network Oriented Intelligent Computation Shenzhen China Department of Computer and Information Science University of Macao Avenida da Universidade Taipa Macao China The College of Computer Science and Technology Guizhou University Guiyang 550025 Guizhou China

Foreground detection methods can be applied to efficiently distinguish foreground objects including moving or static objects from back- ground which is very important in the application of video analysis, especially video surveillance. An excellent background model can obtain a good foreground detection results. A lot of background modeling methods had been proposed, but few comprehensive evaluations of them are available. These methods suffer from various challenges such as illumination changes and dynamic background. This paper first analyzed advantages and disadvantages of various background modeling methods in video analysis applications and then compared their performance in terms of quality and the computational cost. The Change *** （CDnet2014） dataset and another video dataset with different envi- ronmental conditions （indoor, outdoor, snow） were used to test each method. The experimental results sufficiently demonstrated the strengths and drawbacks of traditional and recently proposed state-of-the-art background modeling methods. This work is helpful for both researchers and engineering practitioners. Codes of background modeling methods evaluated in this paper are available ***/***.

关键词： background modeling Video analysis Comprehensive evaluation

Bidirectional background modeling for Video Surveillance

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Journal of Electronic Science and Technology 2012年第3期10卷 232-237页

作者： Chih-Yang Lin Yung-Chen Chou Department of Computer Science and Information Engineering Asia University

Traditional background model methods often require complicated computations, and are sensitive to illumination and shadow. In this paper, we propose a block-based background modeling method, and use our proposed method to combine color and texture characteristics. Suppression and relaxation are the two key strategies to resist illumination changes and shadow disturbance. The proposed method is quite efficient and is capable of resisting illumination changes. Experimental results show that our method is suitable for real-word scenes and real-time applications.

关键词： background modeling Gaussianmixture modeling motion detection.

Vehicle detection algorithm based on codebook and local binary patterns algorithms

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Journal of Central South University 2015年第2期22卷 593-600页

作者：许雪梅周立超墨芹郭巧云 School of Physics and Electronics Central South University

Detecting the moving vehicles in jittering traffic scenes is a very difficult problem because of the complex *** by the color features of the pixel or only by the texture features of image cannot establish a suitable background model for the moving vehicles. In order to solve this problem, the Gaussian pyramid layered algorithm is proposed, combining with the advantages of the Codebook algorithm and the Local binary patterns(LBP) algorithm. Firstly, the image pyramid is established to eliminate the noises generated by the camera shake. Then, codebook model and LBP model are constructed on the low-resolution level and the high-resolution level of Gaussian pyramid, respectively. At last, the final test results are obtained through a set of operations according to the spatial relations of pixels. The experimental results show that this algorithm can not only eliminate the noises effectively, but also save the calculating time with high detection sensitivity and high detection accuracy.

关键词： background modeling Gaussian pyramid Codebook Local binary patterns(LBP) moving vehicle detection

Robust background subtraction in traffic video sequence

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Journal of Central South University 2010年第1期17卷 187-195页

作者：高韬刘正光岳士弘张军梅建强高文春 School of Electrical Engineering and Automation Tianjin University Honeywell (China) Limited

For intelligent transportation surveillance, a novel background model based on Mart wavelet kernel and a background subtraction technique based on binary discrete wavelet transforms were introduced. The background model kept a sample of intensity values for each pixel in the image and used this sample to estimate the probability density function of the pixel intensity. The density function was estimated using a new Marr wavelet kernel density estimation technique. Since this approach was quite general, the model could approximate any distribution for the pixel intensity without any assumptions about the underlying distribution shape. The background and current frame were transformed in the binary discrete wavelet domain, and background subtraction was performed in each sub-band. After obtaining the foreground, shadow was eliminated by an edge detection method. Experimental results show that the proposed method produces good results with much lower computational complexity and effectively extracts the moving objects with accuracy ratio higher than 90%, indicating that the proposed method is an effective algorithm for intelligent transportation system.

关键词： background modeling background subtraction Marr wavelet binary discrete wavelet transform shadow elimination

Exemplar-based video inpainting with large patches

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Journal of Zhejiang University-Science C(Computers and Electronics) 2010年第4期11卷 270-277页

作者： Abbas KOOCHARI Mohsen SORYANI Department of Computer Engineering Iran University of Science and Technology

Inpainting is the process of reconstructing damaged regions of images and video *** study deals with weaknesses of the current video inpainting techniques,when an object is totally damaged,and a framework for video inpainting is *** this framework,the moving object is separated from the background.A large mosaic image is constructed using the moving object and then a patch-based method with large patches is used to fill *** each frame,the inpainted foreground is obtained by placing the object in its *** areas of the stationary background are also filled separately and the final video is produced by composing the inpainted background and object *** for three video sequences with an occluded object show that this approach represents the object in the missing region better than other approaches.

关键词： Video inpainting Patch background modeling Mosaic

Spatially Adaptive Subsampling for Motion Detection

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Tsinghua Science and Technology 2009年第4期14卷 423-433页

作者：夏尔雷章毓晋 Tsinghua National Laboratory for Information Science and Technology Department of Electronic Engineering Tsinghua University

Many video surveillance applications rely on efficient motion detection. However, the algorithms are usually costly since they compute a background model at every pixel of the frame. This paper shows that, in the case of a planar scene with a fixed calibrated camera, a set of pixels can be selected to compute the background model while ignoring the other pixels for accurate but less costly motion detection. The cali- bration is used to first define a volume of interest in the real world and to project the volume of interest onto the image, and to define a spatial adaptive subsampling of this region of interest with a subsampling density that depends on the camera distance. Indeed, farther objects need to be analyzed with more precision than closer objects. Tests on many video sequences have integrated this adaptive subsampling to various motion detection techniques.

关键词： motion detection background modeling adaptive subsampling calibration

Surveillance Video Defogging Algorithm Optimized by background Extraction

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Journal of Systems Science and Information 2022年第4期10卷 410-424页

作者： Hong GUO Xiaochun WANG Hongjun LI College of Sciences Beijing Forestry UniversityBeijing 100083China

To reduce the flicker artifacts caused by video defogging,a surveillance video defogging algorithm based on the background extraction and consistent constraints is ***,an inter frame consistency constraint is constructed and applied to background ***,the extracted background is defogged with an improved static defogging ***,the foreground is extracted using the extracted background and further defogged using constraints of the consistency between the foreground and *** results show that our algorithm can remove fog effectively and preserve the temporal coherence well.

关键词： video defogging video dehazing background modeling temporal coherence

COMBINING SCENE MODEL AND FUSION FOR NIGHT VIDEO ENHANCEMENT

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Journal of Electronics(China) 2009年第1期26卷 88-93页

作者： Li Jing Yang Tao Pan Quan Cheng Yongmei School of Telecommunications Engineering Xidian University Xi ＇ an 710071 China School of Computer Science and Engineering Northwestern Polytechnical University Xi＇ an 710072 China School of Automation Northwestern Polytechnical University Xi＇an 710072 China

This paper presents a video context enhancement method for night surveillance. The basic idea is to extract and fuse the meaningful information of video sequence captured from a fixed camera under different illuminations. A unique characteristic of the algorithm is to separate the image context into two classes and estimate them in different ways. One class contains basic surrounding scene in- formation and scene model, which is obtained via background modeling and object tracking in daytime video sequence. The other class is extracted from nighttime video, including frequently moving region, high illumination region and high gradient region. The scene model and pixel-wise difference method are used to segment the three regions. A shift-invariant discrete wavelet based image fusion technique is used to integral all those context information in the final result. Experiment results demonstrate that the proposed approach can provide much more details and meaningful information for nighttime video.

关键词： Night video enhancement Image fusion background modeling Object tracking

Real-Time Fingertip Detection from Cluttered background for Vision-based HCI

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通讯和计算机（中英文版） 2005年第9期2卷 1-8页

作者： Lianwen Jin Caihong Chen Lixin Zhen Jiancheng Huang South China University of Technology Guangzhou 510640 China Mototora China Research Center Shanghai 200002 China

Vision-based HCI (Human Computer Interaction) is an important technology to make machine more intelligent. Fingertip tracking and detection is the key for many vision-based HCI systems. In this paper, we propose a new fingertip detection approach from cluttered background, and present a new simple but effective foreground segmentation algorithm based on the characteristics of intensity change over the entire image, and a new background updating method based on foreground connection detection. The fingertip position is finally detected based on template matching after the finger foreground image has been successfully segmented. Based on the accurate detection of fingertip, a novel virtual character recognition system is designed. With this fingertip tracking based system, human can input characters to computer using just the movement of his fingertip, without any additional devices such as keyboard, digital pen, so that it provides a novel wireless character inputting modality for HCI application.

关键词： Moving Fingertip Detection background modeling Finger-writing Virtual Character Recognition Human Computer Interaction