• Journal of Broadcast Engineering
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• v.22 no.1
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• pp.70-77
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• 2017

Among available people counting methods, map-based approaches based on moving interest points have shown good performance. However, the stationary people counting is challenging in such methods since all static points of interest are considered as background. To include stationary people in counting, it is needed to discriminate between the static points of stationary people and the background region. In this paper, we propose a people counting method based on using both moving and static points. The proposed method separates the moving and static points by motion information. Then, the static points of the stationary people are classified using foreground mask processing and point pattern analysis. The experimental results reveal that the proposed method provides more accurate count estimation by including stationary people. Also, the background updating is enabled to solve the static point misclassification problem due to background changes.

• Journal of Korea Multimedia Society
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• v.12 no.12
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• pp.1745-1754
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• 2009

PTZ (Pan-Tilt-Zoom) camera based surveillance systems are enlarging their field of application due to their wide observable area. We aimed to detect both static and moving objects in automated working space by using a PTZ camera. For object detection we used background difference method because of the high quality segmentation. However, the method has a problem called 'hole' that is caused by non-continuous surveillance of the PTZ camera and its own characteristics. Moreover, the occlusion which occurs when the moving object overlaps with the static object should be solved for robust object detection. In this paper, we suggest a region-based technique for updating background images thereby overcoming the hole and occlusion problem. Through experiments with real scenes, it was verified that meaningful static and/or moving objects were detected very well.

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.631-636
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• 2009

Foreground segmentation methods have steadily been researched in the field of computer vision. Especially, background subtraction which extracts a foreground image from the difference between the current frame and a reference image, called as "background image" have been widely used for a variety of real-time applications because of low computation and high-quality. However, if the background scene was dynamically changed, the background subtraction causes lots of errors. In this paper, we propose an efficient background subtraction method in dynamic environment with both static and dynamic scene. The proposed method is a hybrid method that uses the conventional background subtraction for static scene and depth information for dynamic scene. Its validity and efficiency are verified by demonstration in dynamic environment, where a video projector projects various images in the background.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.2
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• pp.344-352
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• 2003

An effective algorithm for implementation of which detects moving object from image sequences. predicts the direction of it. and drives the camera in real time is proposed. In static camera, for robust motion detection from a dynamic background scene, the proposed algorithm performs statistical modeling of moving objects and background, and trains the statistical modeling of moving objects and background, and trains the statistical feature of background with the initial parts of sequence which have no moving objects. Active camera moving objects are segmented by following procedure, an improved order adaptive lattice structured linear predictor is used. The proposed algorithm shows robust object tracking results in the environment of static or active camera. It can be used for the unmanned surveillance system, traffic monitoring system, and autonomous vehicle.

• The KIPS Transactions:PartB
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• v.17B no.6
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• pp.405-412
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• 2010

Previous background generation techniques showed bad performance in complex environments since they used only temporal contexts. To overcome this problem, in this paper, we propose a new background generation method which incorporates spatial as well as temporal contexts of the image. This enabled us to obtain 'clean' background image with no moving objects. In our proposed method, first we divided the sampled frame into m*n blocks in the video sequence and classified each block as either static or non-static. For blocks which are classified as non-static, we used MRF framework to model them in temporal and spatial contexts. MRF framework provides a convenient and consistent way of modeling context-dependent entities such as image pixels and correlated features. Experimental results show that our proposed method is more efficient than the traditional one.

• Structural Engineering and Mechanics
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• v.52 no.3
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• pp.485-505
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• 2014

This study aimed to develop an approach to accurately predict the wind models and wind effects of large wind turbines. The wind-induced vibration characteristics of a 5 MW tower-blade coupled wind turbine system have been investigated in this paper. First, the blade-tower integration model was established, which included blades, nacelle, tower and the base of the wind turbine system. The harmonic superposition method and modified blade element momentum theory were then applied to simulate the fluctuating wind field for the rotor blades and tower. Finally, wind-induced responses and equivalent static wind loads (ESWL) of the system were studied based on the modified consistent coupling method, which took into account coupling effects of resonant modes, cross terms of resonant and background responses. Furthermore, useful suggestions were proposed to instruct the wind resistance design of large wind turbines. Based on obtained results, it is shown from the obtained results that wind-induced responses and ESWL were characterized with complicated modal responses, multi-mode coupling effects, and multiple equivalent objectives. Compared with the background component, the resonant component made more contribution to wind-induced responses and equivalent static wind loads at the middle-upper part of the tower and blades, and cross terms between background and resonant components affected the total fluctuation responses, while the background responses were similar with the resonant responses at the bottom of tower.

• JSTS:Journal of Semiconductor Technology and Science
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• v.15 no.6
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• pp.685-694
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• 2015

In this paper, a new dynamic reference scheme is proposed to improve the read voltage margin better than the previous static reference scheme. The proposed dynamic reference scheme can be helpful in compensating not only the background pattern dependence but also the cell position dependence. The proposed dynamic reference is verified by simulating the CMOS-memristor hybrid circuit using the practical CMOS SPICE and memristor Verilog-A models. In the simulation, the percentage read voltage margin is compared between the previous static reference scheme and the new dynamic reference scheme. Assuming that the critical percentage of read voltage margin is 5%, the memristor array size with the dynamic scheme can be larger by 60%, compared to the array size with the static one. In addition, for the array size of $64{\times}64$, the interconnect resistance in the array with the dynamic scheme can be increased by 30% than the static reference one. For the array size of $128{\times}128$, the interconnect resistance with the proposed scheme can be improved by 38% than the previous static one, allowing more margin on the variation of interconnect resistance.

• Journal of the Ergonomics Society of Korea
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• v.9 no.2
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• pp.3-9
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• 1990

The paper concerns with the visual illusion strength for the static and dynamic figures which are generated on computer CRT. The Vertical-Horizontal, Ponzo, and Muller-Lyer illusion are studied under various conditions of type, size, and background angle of figure. And the results are obtained through the Multivariate Analysis of Variance (MANOVA). This paper concludes that the size and background angle of figure generally effect on the visual illusion, and there is a significant difference between figure types. These results can be applied to eliminate the visual illusion in real design.

• Journal of International Academy of Physical Therapy Research
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• v.12 no.2
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• pp.2354-2358
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• 2021

Background: Stroke is a neurological disorder characterized by an impaired static balance. A change in poor posture after stroke may worsen static balance. The balance control through an upright posture may include kinesiology taping of the middle back. Objectives: To investigated the effect of kinesiology taping of middle back on static balance in patients with stroke. Design: A randomized controlled trial. Methods: A total of 10 patients with stroke were divided into two groups. The experimental and control groups received kinesiology taping and placebo taping of the middle back, respectively. After 24 h, static balance (i.e., sway area and path length) was measured in closed eyes condition. Results: The experimental group (kinesiology taping group) showed a significant decrease in sway area and path length after the intervention. In addition, kinesiology taping group showed a significant decrease in sway area and path length compared to the control group. Conclusion: Kinesiology taping of the middle back can improve static balance in stroke patients.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.185-189
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• 2004

For face recognition system, a face detector which can find exact face region from complex image is needed. Many face detection algorithms have been developed under the assumption that background of the source image is quite simple . this means that face region occupy more than a quarter of the area of the source image or the background is one-colored. Color-based face detection is fast but can't be applicable to the images of which the background color is similar to face color. And the algorithm using neural network needs so many non-face data for training and doesn't guarantee general performance. In this paper, A multi-scale, multi-face detection algorithm using PCA is suggested. This algorithm can find most multi-scaled faces contained in static images with small number of training data in reasonable time.