• Journal of the Institute of Electronics and Information Engineers
• /
• v.50 no.6
• /
• pp.228-237
• /
• 2013

In this paper, we propose a normalized cross correlation(NCC)-based multiview background subtraction method which is robust when an object and background have similar color. When the background of the capturing environment is not artificially composed, the regions in the background images which would be occluded by an object tends to have difference colors. The colors of those regions, however, becomes similar when an object enters the capturing environment. Based on this assumption, this paper proposes a concept of GoNCC(Graph of Normalized Cross Correlation). GoNCC is the distribution of NCC between a pixel in an image and pixels related by epipolar constraints with the pixel. The proposed multiview background subtraction method is performed by comparing GoNCC of the current images with the background images. To reduce computational complexity, we perform multiview background subtraction only to the pixels undetermined by single view background subtraction. Experimental results show that the proposed method is more robust to color similarity between an object and background than a single-view background subtraction method and a previous multiview background subtraction method.

• The Mathematical Education
• /
• v.55 no.2
• /
• pp.233-249
• /
• 2016

In this study, we extracted the background meaning of the condition that four points lie on a circle, analyzed textbooks critically and proposed the orientation to improve the content in the textbook. As results, the condition has a realistic background meaning which is 'mathematical modeling of finding a fair location'. The condition has a mathematical background meanings which are 'a first complex situation distinguished from two points and three points', 'the condition described in the perspective of side and angle in order to overcome the disadvantages of the perpendicular bisectors context' and 'being possible to transfer more than five points'. However it is difficult to understand the reason why the condition is on four points in the current textbook. In addition, it is difficult to recognize the connectivity of a circumcenter of triangle. To overcome these problems, we proposed five orientations to improve the content in the textbook.

• Journal of the Korea Society of Computer and Information
• /
• v.11 no.6 s.44
• /
• pp.151-156
• /
• 2006

This paper presents an background edge generation based automatic algorithm for detection of moving objects under moving camera. Background image is generated by rotating the fixed the camera on the tripod horizontally, aligning and reorganizing this images. We develop an efficient approach for robust panoramic background edge generation as well as method of edge matching between input image and background image. We applied the proposed algorithm to real image sequences. The proposed method can be successfully realized in various monitoring systems like intrusion detection as well as video surveillance.

• Wind and Structures
• /
• v.14 no.3
• /
• pp.239-252
• /
• 2011

The wind-induced mean, background and resonant responses of Beijing National Stadium are investigated in this paper. Based on the concepts of potential and kinetic energies, the mode participation factors for the background and the resonant components are presented and the dominant modes are identified. The coupling effect between different modes of the resonant response and the coupling effect between the background and resonant responses are analyzed. The coupling effects between the background and resonant components and between different modes are found all negligible. The mean response is approximately analogous to the peak responses induced by the fluctuating wind. The background responses are significant in the fluctuating responses and it is much larger than the resonant responses at the measurement locations.

• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 2009.01a
• /
• pp.63-66
• /
• 2009

Automatic segmentation of foreground from background in video sequences has attracted lots of attention in computer vision. This paper proposes a novel framework for the background subtraction that the foreground is segmented from the background by directly subtracting a background image from each frame. Most previous works focus on the extraction of more reliable seeds with threshold, because the errors are occurred by noise, weak color difference and so on. Our method has good segmentations from the approximate seeds by using the Random Walks with Restart (RWR). Experimental results with live videos demonstrate the relevance and accuracy of our algorithm.

• Journal of Biomedical Engineering Research
• /
• v.9 no.1
• /
• pp.101-108
• /
• 1988

In this paper the power spectrum of background EEG is estimated by the LMS PHD based on least mean square. At the power spectrum estimatiom, the stocastic process of background EEG is assumed to consist of the nonharmonic sinusoid and the white noise. In the LMS PHD the model parameters are obtained by the least mean square at optimal order which is obtained from the fact that the eigenvalue's fluctuation of autocorrelation matrix of the normal back-ground EEG is smaller at some order than at other order when the power spectrum of background EEG is esitmated by PHD. The optimal order of this model is the 6-th order when the eigenvalue's fluctuation of autocorrelation matrix of background EEG is considered. The estimation results are with compared the results from the Maximum Entropy Spectral Estimation and Pisarenko Harmonic Decomposition. From the comparison results. The LMS PHD is possible to estimate the power spectrum of background EEG.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.5 no.8
• /
• pp.1423-1443
• /
• 2011

Background compensation plays an important role in detecting and isolating object motion in visual tracking. Here, we propose a Genetic Hough Transform, which combines the Hough Transform and Genetic Algorithm, as a method for eliminating background motion. Our method can handle cases in which the background may contain only a few, if any, feature points. These points can be used to estimate the motion between two successive frames. In addition to dealing with featureless backgrounds, our method can successfully handle motion blur. Experimental comparisons of the results obtained using the proposed method with other methods show that the proposed approach yields a satisfactory estimate of background motion.

• Phonetics and Speech Sciences
• /
• v.3 no.3
• /
• pp.173-179
• /
• 2011

The present study was performed to investigate the intelligibility of voice disorder patients by providing the various background noise levels. Four sets of 12-sentence-stimuli produced by 11 voice disorder patients were prepared, and 5 minute-news from radio broadcasting studio were used as a background noise. 30 listeners assigned intelligibility score of each sentence with visual analog scale. Each set of sentences was provided with 20dB, 10dB, 0dB noise (same intensity with stimuli), and, finally, with no noise. As results, as background noise level increased, intelligibility scores were lowered with statistical significance. Even though in the same severity, more loud background noise showed much lower scores than less loud noise. When 10dB noise was provided, intelligibility scores showed the biggest difference among the degree of severity.

• Journal of the Korea Society of Computer and Information
• /
• v.20 no.7
• /
• pp.17-24
• /
• 2015

In this paper, we propose a method to solve ghosting problem. To generate adaptive background, using an exponentially decreasing number of frames, may improve object detection performance. To extract moving objects from the background by using a differential image, detection error may be caused by object rotations or environmental changes. A ghosting problem can be issue-driven when there are outdoor environmental changes and moving objects. We studied that a differential image by adaptive background may reduce the ghosting problem. In experimental results, we test that our method can solve the ghosting problem.

• The Journal of Information Technology
• /
• v.10 no.4
• /
• pp.27-39
• /
• 2007

Object tracking in a real time environment is one of challenging subjects in computer vision area during past couple of years. This paper proposes a method of object detection and tracking using adaptive background estimation in real time environment. To obtain a stable and adaptive background, we combine 3-frame differential method and running average single gaussian background model. Using this background model, we can successfully detect moving objects while minimizing false moving objects caused by noise. In the tracking phase, we propose a matching criteria where the weight of position and inner brightness distribution can be controlled by the size of objects. Also, we adopt a Kalman Filter to overcome the occlusion of tracked objects. By experiments, we can successfully detect and track objects in real time environment.