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RISS 인기검색어
- 검색키워드
- 저자 : Yuming Fang (검색결과 5 건)
- 무료
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Abnormal Event Detection Based on Saliency Information
Zhijun Fang,Fengchang Fei,Yuming Fang,Lei Shu,Wanggen Wan 보안공학연구지원센터 2015 International Journal of Multimedia and Ubiquitous Vol.10 No.9
Abnormal event detection is a challenging task in video analysis. In this paper, we propose a new abnormal event detection algorithm for surveillance videos. It is well accepted that human eyes are extremely sensitive to abnormal events and they can quickly pay attention to the locations of these abnormal events in visual scenes. Thus, the characteristics of the Human Visual System (HVS) can be used for abnormal event detection. By exploiting the characteristics of the HVS, we propose an abnormal event detection algorithm based on saliency information. Firstly, the saliency information is extracted from video frames based on the feature contrast. The motion information of video frames is calculated by the multi-scale histogram optical flow (MHOF). Based on the features of saliency information and MHOF, the Support Vector Machine (SVM) is used to train and predict the abnormal events in visual scenes. Experimental results show that the proposed abnormal event detection method can obtain much better performance than the existing ones over the public video database.
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A Novel Objective Quality Assessment for Super-Resolution Images
Lei Shu,Yuming Fang,Zhijun Fang,Yong Yang,Fengchang Fei,Naixue Xiong 보안공학연구지원센터 2016 International Journal of Signal Processing, Image Vol.9 No.5
A novel objective quality assessment method is proposed for super-resolution images in this manuscript. We not only estimate the preserved information of each spatial location in the super-resolution image by structural similarity, but also compute the local phase coherence (LPC) with which we can detect the image blur in the super-resolution image. After the preserved structural information and blur information is obtained, an overall evaluation of visual quality of the super-resolution image can be computed. Experimental results show that the proposed objective quality assessment method can be used in the real applications with the original high-resolution images unavailable.
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Stabilization of Nonlinear Switched Systems with Distributed Time-delay: The Discrete-time Case
Chaochen Wang,Xiaoli Fang,Lifeng Ma,Jie Zhang,Yuming Bo 제어·로봇·시스템학회 2021 International Journal of Control, Automation, and Vol.19 No.12
This paper investigates the stabilization problem of nonlinear switched systems subject to the distributed time-delay. The considered nonlinear switched systems are quite general whose dynamics are affected by bothexogenous noises and distributed time-delay. The purpose of the addressed problem is to propose a state feedback control law such that, the closed-loop system is exponentially stable in the mean square sense and meanwhile, therequired weighted L2 gain is achieved. By resorting to the Lyapunov functional method in combination with the average dwell time approach, sufficient conditions are provided for the existence of the desired control schemein terms of the feasibility of certain Hamilton-Jacobi inequalities (HJIs). Within the established framework, the required feedback controller gains can be obtained by solving the series of HJIs. Finally, an illustrative numericalexample is provided to demonstrate the effectiveness of the developed control algorithm.
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Song, Enming,Li, Rui,Jin, Xin,Du, Haina,Huang, Yuming,Zhang, Jize,Xia, Yu,Fang, Hui,Lee, Yoon Kyeung,Yu, Ki Jun,Chang, Jan-Kai,Mei, Yongfeng,Alam, Muhammad A.,Huang, Yonggang,Rogers, John A. American Chemical Society 2018 ACS NANO Vol.12 No.10
<P>Biomedical implants that incorporate active electronics and offer the ability to operate in a safe, stable fashion for long periods of time must incorporate defect-free layers as barriers to biofluid penetration. This paper reports an engineered material approach to this challenge that combines ultrathin, physically transferred films of silicon dioxide (t-SiO<SUB>2</SUB>) thermally grown on silicon wafers, with layers of hafnium oxide (HfO<SUB>2</SUB>) formed by atomic layer deposition and coatings of parylene (Parylene C) created by chemical vapor deposition, as a dual-sided encapsulation structure for flexible bioelectronic systems. Accelerated aging tests on passive/active components in platforms that incorporate active, silicon-based transistors suggest that this trilayer construct can serve as a robust, long-lived, defect-free barrier to phosphate-buffered saline (PBS) solution at a physiological pH of 7.4. Reactive diffusion modeling and systematic immersion experiments highlight fundamental aspects of water diffusion and hydrolysis behaviors, with results that suggest lifetimes of many decades at physiological conditions. A combination of ion-diffusion tests under continuous electrical bias, measurements of elemental concentration profiles, and temperature-dependent simulations reveals that this encapsulation strategy can also block transport of ions that would otherwise degrade the performance of the underlying electronics. These findings suggest broad utility of this trilayer assembly as a reliable encapsulation strategy for the most demanding applications in chronic biomedical implants and high-performance flexible bioelectronic systems.</P> [FIG OMISSION]</BR>
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Sub Oriented Histograms of Local Binary Patterns for Smoke Detection and Texture Classification
( Feiniu Yuan ),( Jinting Shi ),( Xue Xia ),( Yong Yang ),( Yuming Fang ),( Rui Wang ) 한국인터넷정보학회 2016 KSII Transactions on Internet and Information Syst Vol.10 No.4
Local Binary Pattern (LBP) and its variants have powerful discriminative capabilities but most of them just consider each LBP code independently. In this paper, we propose sub oriented histograms of LBP for smoke detection and image classification. We first extract LBP codes from an image, compute the gradient of LBP codes, and then calculate sub oriented histograms to capture spatial relations of LBP codes. Since an LBP code is just a label without any numerical meaning, we use Hamming distance to estimate the gradient of LBP codes instead of Euclidean distance. We propose to use two coordinates systems to compute two orientations, which are quantized into discrete bins. For each pair of the two discrete orientations, we generate a sub LBP code map from the original LBP code map, and compute sub oriented histograms for all sub LBP code maps. Finally, all the sub oriented histograms are concatenated together to form a robust feature vector, which is input into SVM for training and classifying. Experiments show that our approach not only has better performance than existing methods in smoke detection, but also has good performance in texture classification.
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