• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.3
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• pp.387-391
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• 2008

For the detection of moving objects, background subtraction methods are widely used. In case the background has variation, we need to update the background in real-time for the reliable detection of foreground objects. Gaussian mixture model (GMM) combined with probabilistic learning is one of the most popular methods for the real-time update of the background. However, it does not work well in the complex and dynamic backgrounds with high traffic regions. In this paper, we propose a new method for modelling and updating more reliably the complex and dynamic backgrounds based on the probabilistic learning and the layered processing.

• Journal of Power Electronics
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• v.19 no.2
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• pp.509-518
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• 2019

A novel islanding detection method is proposed in this paper. It is based on a frequency drooping PLL, which was presented in a previous work. The cause of errors in the non-detection zone (NDZ) of conventional frequency disturbance islanding detection methods (IDM) is analyzed. A frequency drooping phase-locked-loop (FD-PLL) is introduced into a single-phase grid-connected inverter (SPGCI), which can guarantee that grid current is in phase with the grid voltage. A novel FD-PLL IDM is proposed by improving this PLL. In order to verify the performance of the proposed FD-PLL IDM, a full performance comparison between the proposed IDM and typical existing active frequency drift IDMs is carried out, which includes both dynamic performance and steady performance. With the same NDZ, the total harmonic distortion of the grid-current in the dynamic process and steady state is analyzed. The proposed FD-PLL IDM, regardless of the dynamic or steady process, has the best power quality. Experimental and simulation results verify that the proposed FD-PLL IDM has excellent performance.

• Journal of the Korea Computer Graphics Society
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• v.25 no.2
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• pp.11-18
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• 2019

In this paper, we propose a framework that can perform acceleration collision detection efficiently by using a cone based collision area in a particle-based system which requires collision detection with many objects. Three conditions determine particle and cone-based collision regions: 1) If there is a cone position within the radius of the adjacent particle, 2) In the case where the position of the adjacent particle exists in the cone area, 3) When adjacent particles exist between two vectors forming a cone area. As a result, it is defined that when the above conditions are all satisfied, the particle and the region of a cone have collided. In this paper, we automatically update the area of the cone, which is the collision detection area, according to the particle movement. Determine the direction and length of the cone based on the position and velocity of the particle to calculate the dynamic change of the cone. Collision detection is performed quickly using only the particles in the finally calculated area. The acceleration method proposed in this paper is simple to implement because it is executed with a closed form equation instead of explicitly creating the tree data structure, and collision inspection performance is improved in all results.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.4
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• pp.758-766
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• 2003

This paper proposes a tree-based hierarchical image mosaicing system using camera and object parameters for efficient video database construction. Gray level histogram difference and average intensity difference are proposed for scene change detection of input video. Camera parameter measured by utilizing least sum of square difference and affine model, and difference image is used for similarity measure of two input images. Also, dynamic objects are searched by through macro block setting and extracted by using region splitting and 4-split detection methods. Dynamic trajectory evaluation function is used for expression of dynamic objects, and blurring is performed for construction of soft and slow mosaic image.

• The Korean Journal of Applied Statistics
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• v.24 no.5
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• pp.979-986
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• 2011

A linear regression method is commonly used to analyze data because of its simplicity and applicability; however, it is well known that data may contain some outliers and influential cases that may have a harmful effect on a statistical analysis. Thus detection and examination of outliers or influential cases are important parts of data analysis. In detecting multiple outliers, masking effects usually occur and make it difficult to identify the true outliers. We propose to use dynamic plots as a method resistant to masking effect. The procedure using dynamic plots is useful to find appropriate basic sets with which a dependent outliers detection method start and detect a true outliers set. Examples are given to demonstrate the effectiveness of the suggested idea.

• The Proceeding of the Korean Institute of Electromagnetic Engineering and Science
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• v.11 no.4
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• pp.39-52
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• 2000

A design of 2 stage S-DLVA(successive detector log video amplifier) was studied to detect wide dynamic radar pulse ranging from -70 ㏈m to 0㏈m. A basic design idea was focused on the linear detection in logarithmic scale of wide dynamic range radar pulses from nosie-like weak power of -70 ㏈m to relatively high power 0 ㏈m. It is highly formidable, since it requires high speed detection less than 10 nsec over the operating frequency ranges from 6 to 18 ㎓. A limiter diode, a tunnel diode and an L17-C were used as a protecting device, a detector diode and a log video amplifier in companion as a single stage detector to give voltage output proportional to the input power of about 35 ㏈ dynamic range. A protype of 2-stage DLVA having one more single stage detector was fabricated with a 32 ㏈ low noise amplifier and a 3 ㏈ hybrid coupler to provide total 70 ㏈ dynamic range detection. The logging characteristics were measured to have log slope of 25m.V/㏈ against 70 ㏈ logging range from -55 ㏈m to +15 ㏈m, the log linearity of within +/- 1.5 ㏈, and tangential sensitivity was at -63 ㏈m. The pulse dynamics of rise time and recovery time were measured as 50 nsec and 1.2 $\mu$sec, respectively. The reason might be due to the parasitic capacitances of packaged limiter, tunnel diode, and L17-C.

• International conference on construction engineering and project management
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• 2024.07a
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• pp.367-374
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• 2024

The detection and tracking of construction workers in building sites generate valuable data on unsafe behavior, work productivity, and construction progress. Many computer vision-based tracking approaches have been investigated and their capabilities for tracking construction workers have been tested. However, the dynamic nature of real-world construction environments, where workers wear similar outfits and move around in often cluttered and occluded regions, has severely limited the accuracy of these methods. Herein, to enhance the performance of vision-based tracking, a new framework is proposed which seamlessly integrates three computer vision components: detection, tracking, and re-identification (DTR). In DTR, a tracking algorithm continuously tracks identified workers using a detector and tracker in combination. Then, a re-identification model extracts visual features and utilizes them as appearance descriptors in subsequent frames during tracking. Empirical results demonstrate that the proposed method has excellent multi-object-tracking accuracy with better accuracy than an existing approach. The DTR framework can efficiently and accurately monitor workers, ensuring safer and more productive dynamic work environments.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.2
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• pp.407-414
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• 2007

A sensor fault detection scheme(SFDS) for a class of nonlinear systems that can be represented by Takagi-Sugeno fuzzy model is proposed. Basically, the SFDS may be considered as a multiple observer scheme(MOS) in which the bank of state observers and the detection & isolation logic are included. However, the proposed scheme has two great differences from the conventional MOSs. First, the proposed scheme includes fuzzy fault detection observers(FFDO) that are constructed based on the T-S fuzzy model that provides very good approximation to nonlinear dynamic systems. Secondly, unlike the conventional MOS, the FFDOS are driven not parallelly but sequentially according to the predetermined sequence to avoid the massive computational burden, which is known to be the biggest obstacle to the practical application of the multiple observer based FDI schemes. During the operating time, each FFDO generates the residuals carrying the information of a specified fault, and the corresponding fault detection logic unit performs the logical operations to detect and isolate the fault of interest. The proposed scheme is applied to an inverted pendulum control system for sensor fault detection/isolation. Simulation study shows the practical feasibility of the proposed scheme.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.4A
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• pp.356-363
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• 2002

Video scene segmentation is fundamental role for content based video analysis and many kinds of scene segmentation schemes have been proposed in previous researches. However, there is a problem, which is to find optimal threshold value according to various kinds of movies and its content because only fixed single threshold value usually used for cut detection. In this paper, we proposed the variable dynamic threshold method, which change the threshold value by a probability distribution of cut detection interval and information of frame feature differences and cut detection interval in previous cut detection is used to determine the next cut detection. For this, we present a cut detection algorithm and a parameter generation method to change the threshold value in runtime. We also show the proposed method, which can minimize fault alarm rate than the existing methods efficiently by experimental results.

• Journal of Biomedical Engineering Research
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• v.8 no.2
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• pp.177-188
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• 1987

Detection of left ventricular boundary for the functional analysis of LV(left ventricle) is obtained using automatic boundary detection algorithm based on dynamic program ming method. This scheme reduces the edge searching time and ensures connective edge detection, since it does not require general edge operator, edge thresholding and linking process of other edge detection methods. The left ventricular diastolic volume and systolic volume were computed after this automatic boundary detection, and these volume data were applied to analyze LV ejection fraction.