• Title/Summary/Keyword: Mean-Shift

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A Study on Image inpainting using Mean-Shift Algorithm (Mean-Shift Algorithm을 이용한 Image inpainting에 관한 연구)

  • Gong, Jae-Woong;Jung, Jae-Jin;Hwang, Eui-Sung;Kim, Tae-Hyoung;Kim, Doo-Yung
    • Proceedings of the Korea Institute of Convergence Signal Processing
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    • 2006.06a
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    • pp.49-52
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    • 2006
  • 오늘날 컴퓨터의 발달과 인터넷의 확산으로 멀티미디어 컨텐츠의 보급이 급격히 확대되고 있으며, 이들 컨텐츠에는 원거리 화상회의, 감시시스템, 주문형 비디오(VOD), 주문형 뉴스(NOD), 디지털 편집 시스템 등 동영상이 포함되어 있다. 이처럼 동영상은 정보교환과 정보표현의 매개물로서 중요한 역할을 한다. 그러나 이와 같은 동영상은 노이즈나 전송과정 중 발생하는 문제 등으로 인해 항상 좋은 품질을 보장되지 않는다. 이런 훼손된 영상을 원영상으로 복원하거나 사용자가 제거 혹은 복원하고자 하는 영역을 지정 처리함으로서 다양한 정보를 획득할 수 있다. 일반적으로 pc에서 사용되어지는 대부분의 동영상은 $15fps{\sim}30fps$이다. 대부분의 동영상 편집 기술은 각각의 frame을 추출하여 수동적으로 처리하므로 비용과 시간이 많이 든다. 이런 단점을 해결하기 위해 여러 방법이 기존에 시도되고 있다. 제거 혹은 복원하고자 하는 영역을 전 frame에서 처리하기 위해 움직임 검출 및 추적기법이 사용되며, 제거 혹은 복원하기 위해 median filtering, image inpainting 처리 방법들이 있다. 본 연구에서는 사용자에 의해 미리 정의된 바운딩 박스내의 객체를 추적하여 객체의 중심값을 찾는 mean-shift algorithm을 이용하여 움직이는 객체를 추적하였고 image Inpainting algorithm을 이용하여 훼손된 영역을 복원하거나 제거하고자 하는 객체를 제거하였다.

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Outlier Detection in Growth Curve Model Using Mean-Shift Model (평균이동모형을 이용한 성장곡선모형의 이상점 진단에 관한 연구)

  • Shim, Kyu-Bark
    • Journal of the Korean Data and Information Science Society
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    • v.10 no.2
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    • pp.369-385
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    • 1999
  • For the growth curve model with arbitrary covariance structure, known as unstructured covariance matrix, the problems of detecting outliers are discussed in this paper. In order to detect outliers in the growth curve model, the likelihood ratio testing statistics in mean shift model is established and its distribution is derived. After we detected outliers in growth curve model, we test homo and/or hetero-geneous covariance matrices using PSR Quasi-Bayes Criterion. For illustration, one numerical example is discussed, which compares between before and after outlier deleting.

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Design of a Recognizing System for Vehicle's License Plates with English Characters

  • Xing, Xiong;Choi, Byung-Jae;Chae, Seog;Lee, Mun-Hee
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.9 no.3
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    • pp.166-171
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    • 2009
  • In recent years, video detection systems have been implemented in various infrastructures such as airport, public transportation, power generation system, water dam and so on. Recognizing moving objects in video sequence is an important problem in computer vision, with applications in several fields, such as video surveillance and target tracking. Segmentation and tracking of multiple vehicles in crowded situations is made difficult by inter-object occlusion. In the system described in this paper, the mean shift algorithm is firstly used to filter and segment a color vehicle image in order to get candidate regions. These candidate regions are then analyzed and classified in order to decide whether a candidate region contains a license plate or not. And then some characters in the license plate is recognized by using the fuzzy ARTMAP neural network, which is a relatively new architecture of the neural network family and has the capability to learn incrementally unlike the conventional BP network. We finally design a license plate recognition system using the mean shift algorithm and fuzzy ARTMAP neural network and show its performance via some computer simulations.

Movement Detection Algorithm Using Virtual Skeleton Model (가상 모델을 이용한 움직임 추출 알고리즘)

  • Joo, Young-Hoon;Kim, Se-Jin
    • Journal of the Korean Institute of Intelligent Systems
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    • v.18 no.6
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    • pp.731-736
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    • 2008
  • In this paper, we propose the movement detection algorithm by using virtual skeleton model. To do this, first, we eliminate error values by using conventioanl method based on RGB color model and eliminate unnecessary values by using the HSI color model. Second, we construct the virtual skeleton model with skeleton information of 10 peoples. After matching this virtual model to original image, we extract the real head silhouette by using the proposed circle searching method. Third, we extract the object by using the mean-shift algorithm and this head information. Finally, we validate the applicability of the proposed method through the various experiments in a complex environments.

Smart Photo Clustering Based on Dominant Color Histogram Feature and Mean-Shift Clustering (주 색상 히스토그램 특징과 Mean-Shift 알고리즘을 사용한 사진 자동분류)

  • Na, In-Seop;Choi, Jun-Yong;Cho, Wan-Hyun;Kim, Soo-Hyung
    • Proceedings of the Korea Information Processing Society Conference
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    • 2012.11a
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    • pp.633-636
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    • 2012
  • 최근 디지털카메라와 스마트 폰 등의 모바일 기기가 급속도로 발전 하면서 언제, 어디서나 손쉽게 사진을 찍을 수 있게 되었다. 이런 환경의 변화는 수없이 많은 사진을 양산하게 되었고, 손쉽게 많이 찍은 사진에 대한 분류에 불필요한 시간을 많이 보내게 되었다. 따라서 보다 편리하게 촬영된 사진들을 분류 관리하기에 적합한 자동화된 프로그램이 필요하게 되었다. 이 논문에서는 GPS나 시간 등의 메타 정보에 의존하지 않고 오직 사진의 주 색상을 이용한 히스토그램 특징과 Mean Shift 분류기를 사용하여 대략적인 분류를 시도하려했다. 실험결과를 토대로 살펴보면, 제안된 방법은 사진의 주 색상이 확실한 경우는 잘 분류할 수 있지만 여러 가지 색상이 복잡하게 혼합된 경우와 주 색상을 찾기 어려운 경우에는 분류에 한계가 있음을 알 수 있었다. 따라서 제안된 알고리즘은 사진과 영상들을 개략적인 분류를 실시할 때 주 색상 히스토그램특징이 의미 있는 전역적 특징(Global Feature)중의 하나로 생각된다.

Plantar Pressure in Skilled and Unskilled Players during Baseball Batting (야구 타격시 숙련자와 미숙련자의 족저압력 분석)

  • Moon, Won-Ho;Lee, Joong-Sook;Kim, Chang-Hyun;Jang, Young-Min;Jeong, Jin-Woo
    • Korean Journal of Applied Biomechanics
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    • v.23 no.1
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    • pp.25-35
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    • 2013
  • This study examined 24 right-handed amateur baseball players. Twelve who had played baseball for more than 6 years were grouped as skilled players, while 12 who had played for 1-3 years were the unskilled player group. The swing motion was divided into four event phases: stance, backswing, impact, and follow-through. The mean and maximum plantar pressure, center of pressure, and ground reaction force were measured during each event phase. The mean and standard deviations for each variables were calculated and differences were validated with the independent sample t-test. A p-value <0.05 was considered statistically significant. The results were as follows. 1)The ideal stance is a stable, balanced position with more than 65% of weight on the right foot. There was significant difference in mean left plantar pressure, while the maximal plantar pressure and mean right plantar pressure did not differ significant. 2)The effective backswing of a skilled player is comprised a rightward shift in weight to build maximum energy. More than 90% of the weight was on the right foot. There was a significant difference in the mean left plantar pressure, while the maximal plantar pressure and mean right plantar pressure did not differ significantly. 3) For an effective impact, a rapid shift in weight to the left foot is essential, so that a power hit is obtained. Significant difference in the mean and maximum plantar pressures of both feet were observed. 4)Follow-through requires wight balance, more on the right than the left, without leaning leftward. There was no significant difference in the mean or maximum plantar pressure. 5)The center of plantar pressure should move from the center of the foot to the toe. 6)The analyses of the ground reaction force suggest that a good swing involves a gradual shift in weight to the right side and a rapid leftward shift at impact. Good balance, with the center of gravity on the right side at follow-through, is also required.

A Real-Time Head Tracking Algorithm Using Mean-Shift Color Convergence and Shape Based Refinement (Mean-Shift의 색 수렴성과 모양 기반의 재조정을 이용한 실시간 머리 추적 알고리즘)

  • Jeong Dong-Gil;Kang Dong-Goo;Yang Yu Kyung;Ra Jong Beom
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.42 no.6
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    • pp.1-8
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    • 2005
  • In this paper, we propose a two-stage head tracking algorithm adequate for real-time active camera system having pan-tilt-zoom functions. In the color convergence stage, we first assume that the shape of a head is an ellipse and its model color histogram is acquired in advance. Then, the min-shift method is applied to roughly estimate a target position by examining the histogram similarity of the model and a candidate ellipse. To reflect the temporal change of object color and enhance the reliability of mean-shift based tracking, the target histogram obtained in the previous frame is considered to update the model histogram. In the updating process, to alleviate error-accumulation due to outliers in the target ellipse of the previous frame, the target histogram in the previous frame is obtained within an ellipse adaptively shrunken on the basis of the model histogram. In addition, to enhance tracking reliability further, we set the initial position closer to the true position by compensating the global motion, which is rapidly estimated on the basis of two 1-D projection datasets. In the subsequent stage, we refine the position and size of the ellipse obtained in the first stage by using shape information. Here, we define a robust shape-similarity function based on the gradient direction. Extensive experimental results proved that the proposed algorithm performs head hacking well, even when a person moves fast, the head size changes drastically, or the background has many clusters and distracting colors. Also, the propose algorithm can perform tracking with the processing speed of about 30 fps on a standard PC.

Comparison of Subjective Symptoms of workers in Rapidly and Weekly Rotating Shift Systems (교대주기가 다른 두 유리제조업체 3교대 근무자들의 자각증상 비교)

  • Jung, Young-Yeon;Choi, Gwang-Seo;Woo, Kuck Hyeun;Han, Gu-Wung
    • Journal of Preventive Medicine and Public Health
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    • v.25 no.4 s.40
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    • pp.374-385
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    • 1992
  • Some circadian rhythms can become disorgnized due to rotating shift work. This lack of organization, termed desynchronization, can produce a group of symptoms such as insomnia, GI disturbance and fatigue among many rotating shift workers. The magnitude of these symptoms are influenced by personal and environmental factors and the patterns of shift work. This study was carried out to investigate the subjective symptoms related to rotational schedules of shift work after personal and environmental factors adjusted. 182 male workers in rapidly rotating shift system and 86 male workers in weekly rotating shift system were conducted the questionnaire on personal factors and subjective sleep, GI and fatigue symptoms. Major findings obtained from this study are as follows: 1. The symptoms of 'feeling tired at work' and 'being irritable' were more frequent in weekly rotating shift workers (P<0.05), and the mean of symptom score was significantly higher in weekly rotating shift workers(P<0.01). 2. According to 6 hours of sleeping which is a definite elevation point of fatigue, there was not a significant difference between two groups in sleeping hours. Among workers in rapidly rotating shift system, the mean of symptom score was significatly higher in workers of less than 6 hours of sleeping(P<0.05), but it was not different among weekly rotating shift workers. 3. The symptoms of GI disturbance were more frequent in weekly rotating shift workers but statistically not significant. 4. The positive rate of mental and physical fatigue symptoms were significantly higher in weekly rotating shift workers(P<0.01) and mental and physical fatigue symptoms were more frequent in them (P<0.01). 5. After the effect of the factors that were significantly different between two groups by $X^2-test$ were controlled, the mean score of sleep disturbance was significantly higher in weekly rotating shift workers (P<0.01) and mental physical fatigue symptoms were more frequent in them (P<0.01). Based on these study results, subjective symptoms were more common in the weekly rotating shift workers. In future, medical examination and laboratory test will be also administered to evaluate a more accurate health outcomes and the review of current shift schedules will be required.

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ACMs-based Human Shape Extraction and Tracking System for Human Identification (개인 인증을 위한 활성 윤곽선 모델 기반의 사람 외형 추출 및 추적 시스템)

  • Park, Se-Hyun;Kwon, Kyung-Su;Kim, Eun-Yi;Kim, Hang-Joon
    • Journal of Korea Society of Industrial Information Systems
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    • v.12 no.5
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    • pp.39-46
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    • 2007
  • Research on human identification in ubiquitous environment has recently attracted a lot of attention. As one of those research, gait recognition is an efficient method of human identification using physical features of a walking person at a distance. In this paper, we present a human shape extraction and tracking for gait recognition using geodesic active contour models(GACMs) combined with mean shift algorithm The active contour models (ACMs) are very effective to deal with the non-rigid object because of its elastic property. However, they have the limitation that their performance is mainly dependent on the initial curve. To overcome this problem, we combine the mean shift algorithm with the traditional GACMs. The main idea is very simple. Before evolving using level set method, the initial curve in each frame is re-localized near the human region and is resized enough to include the targe region. This mechanism allows for reducing the number of iterations and for handling the large object motion. The proposed system is composed of human region detection and human shape tracking modules. In the human region detection module, the silhouette of a walking person is extracted by background subtraction and morphologic operation. Then human shape are correctly obtained by the GACMs with mean shift algorithm. In experimental results, the proposed method show that it is extracted and tracked efficiently accurate shape for gait recognition.

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The Effects of Fatigue on Cognitive Performance in Police Officers and Staff During a Forward Rotating Shift Pattern

  • Taylor, Yvonne;Merat, Natasha;Jamson, Samantha
    • Safety and Health at Work
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    • v.10 no.1
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    • pp.67-74
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    • 2019
  • Background: Few studies have examined the effects of a forward rotating shift pattern on police employee performance and well-being. This study sought to compare sleep duration, cognitive performance, and vigilance at the start and end of each shift within a three-shift, forward rotating shift pattern, common in United Kingdom police forces. Methods: Twenty-three police employee participants were recruited from North Yorkshire Police (mean age, 43 years). The participants were all working the same, 10-day, forward rotating shift pattern. No other exclusion criteria were stipulated. Sleep data were gathered using both actigraphy and self-reported methods; cognitive performance and vigilance were assessed using a customized test battery, comprising five tests: motor praxis task, visual object learning task, NBACK, digital symbol substitution task, and psychomotor vigilance test. Statistical comparisons were conducted, taking into account the shift type, shift number, and the start and end of each shift worked. Results: Sleep duration was found to be significantly reduced after night shifts. Results showed a significant main effect of shift type in the visual object learning task and NBACK task and also a significant main effect of start/end in the digital symbol substitution task, along with a number of significant interactions. Conclusion: The results of the tests indicated that learning and practice effects may have an effect on results of some of the tests. However, it is also possible that due to the fast rotating nature of the shift pattern, participants did not adjust to any particular shift; hence, their performance in the cognitive and vigilance tests did not suffer significantly as a result of this particular shift pattern.