• Title/Summary/Keyword: Visual tracking

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Current Barriers of Obesity Management of Children Using Community Child Care Centers and Potential Possibility of Utilizing Mobile Phones: A Qualitative Study for Children and Caregivers (지역아동센터 이용 어린이의 비만관리의 한계점과 모바일폰의 잠재적인 활용 가능성: 어린이와 보호자 대상의 질적 연구)

  • Lee, Bo Young;Park, Mi-Young;Kim, Kirang;Shim, Jea Eun;Hwang, Ji-Yun
    • Korean Journal of Community Nutrition
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    • v.25 no.3
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    • pp.189-203
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    • 2020
  • Objectives: This study was performed to identify the current barriers of obesity management for children using Community Child Care Centers and their caregivers (parents and teachers working in the Centers). Further, this study explored the possibility of utilizing a mobile phone application for tailored obesity prevention and management programs to overcome the current difficulties associated with children's obesity management. Methods: The qualitative data were collected through in-depth interviews with 20 obese and overweight children or children who wanted to participate in this study using Community Child Care Centers, 12 teachers working at the Centers, and a focus group interview with five parents of children using the Centers. Data were analyzed with a thematic approach categorizing themes and sub-themes based on the transcripts. Results: The current barriers of obesity management of obese and overweight children using Community Child Care Centers were lack of self-directed motivation regarding obesity management (chronic obesity-induced lifestyles and reduced self-confidence due to stigma) and lack of support from households and Community Child Care Centers (latchkey child, inconsistency in dietary guidance between the Center and household, repetitive pressure to eat, and absence of regular nutrition education). Mobile phone applications may have potential to overcome the current barriers by providing handy and interesting obesity management based on visual media (real-time tracking of lifestyles using behavior records and social support using gamification), environmental support (supplementation of parental care and network-based education between the Community Child Care Center and household), and individualized intervention (encouragement of tailored and gradual changes in eating habits and tailored goal setting). It is predicted that the real-time mobile phone program will provide information for improving nutritional knowledge and behavioral skills as well as lead to sustainable children's coping strategies regarding obesity management. In addition, it is expected that environmental factors may be improved by network-based education between the Community Child Care Centers and households using the characteristics of mobile phones, which are free from space and time constraints. Conclusions: The tailored education program for children using Community Child Care Centers based on mobile phones may prevent and reduce childhood obesity by overcoming the current barriers of obesity management for children, providing environmental and individualized support to promote healthy lifestyles and quality of life in the future.

Method Extracting Observation Data by Spatial Factor for Analysis of Selective Attention of Vision (시각의 선택적 주의집중 분석을 위한 공간요소별 주시데이터 추출방법)

  • Kim, Jong-Ha;Kim, Ju-Yeon
    • Science of Emotion and Sensibility
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    • v.18 no.4
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    • pp.3-14
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    • 2015
  • This study has extracted observation data by spatial factor for the analysis of subjects' selective attention with the objects of public space at the entrance of subway stations. The methods extracting observation data can be summarized as the following. First, the frequency analysis by lattice was prevalent for those methods, but there is a limitation to the analysis of the observation data. On the contrary, the method extracting observation data by factor applied in this study can make it clear if any sight is concentrated on any particular factors in a space. Second, the results from the extracted data corresponding to the observation area can be objectified while the method setting up the observation area by applying the radius of fovea. Third, time-sequential trace of observation results of relevant factors was possible through hourly analysis of spatial factors. The consideration of the results of "corresponding spatial scope" which is the object of this study will reveal that the more the observation time, the less the degree of attention it receives. Fourth, the frequency of observation superiority was applied for the analysis of the sections with selective attention by time scope; this revealed that men and women had intensive observation in time scope I (52.4 %) and in time scope IV (24.0 %), respectively.

Object Detection Algorithm Using Edge Information on the Sea Environment (해양 환경에서 에지 정보를 이용한 물표 추출 알고리즘)

  • Jeong, Jong-Myeon;Park, Gyei-Kark
    • Journal of the Korea Society of Computer and Information
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    • v.16 no.9
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    • pp.69-76
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    • 2011
  • According to the related reports, about 60 percents of ship collisions have resulted from operating mistake caused by human factor. Specially, the report said that negligence of observation caused 66.8 percents of the accidents due to a human factor. Hence automatic detection and tracking of an object from an IR images are crucial for safety navigation because it can relieve officer's burden and remedies imperfections of human visual system. In this paper, we present a method to detect an object such as ship, rock and buoy from a sea IR image. Most edge directions of the sea image are horizontal and most vertical edges come out from the object areas. The presented method uses them as a characteristic for the object detection. Vertical edges are extracted from the input image and isolated edges are eliminated. Then morphological closing operation is performed on the vertical edges. This caused vertical edges that actually compose an object be connected and become an object candidate region. Next, reference object regions are extracted using horizontal edges, which appear on the boundaries between surface of the sea and the objects. Finally, object regions are acquired by sequentially integrating reference region and object candidate regions.

The Effect of Emotional Sounds on Multiple Target Search (정서적인 소리가 다중 목표 자극 탐색에 미치는 영향)

  • Kim, Hannah;Han, Kwang Hee
    • Korean Journal of Cognitive Science
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    • v.26 no.3
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    • pp.301-322
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    • 2015
  • This study examined the effect of emotional sounds on satisfaction of search (SOS). SOS occurs when detection of a target results in a lesser chance of finding subsequent targets when searching for an unknown number of targets. Previous studies have examined factors that may influence the phenomenon, but the effect of emotional sounds is yet to be identified. Therefore, the current study investigated how emotional sound affects magnitude of the SOS effect. In addition, participants' eye movements were recorded to determine the source of SOS errors. The search display included abstract T and L-shaped items on a cloudy background and positive and negative sounds. Results demonstrated that negative sounds produced the largest SOS effect by definition, but this was due to superior accuracy in low-salient single target trials. Response time, which represents efficiency, was consistently faster when negative sounds were provided, in all target conditions. On-target fixation classification revealed scanning error, which occurs because targets are not fixated, as the most prominent type of error. These results imply that the two dimensions of emotion - valence and arousal - interactively affect cognitive performance.

A Study on the Automatic Detection of Railroad Power Lines Using LiDAR Data and RANSAC Algorithm (LiDAR 데이터와 RANSAC 알고리즘을 이용한 철도 전력선 자동탐지에 관한 연구)

  • Jeon, Wang Gyu;Choi, Byoung Gil
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.31 no.4
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    • pp.331-339
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    • 2013
  • LiDAR has been one of the widely used and important technologies for 3D modeling of ground surface and objects because of its ability to provide dense and accurate range measurement. The objective of this research is to develop a method for automatic detection and modeling of railroad power lines using high density LiDAR data and RANSAC algorithms. For detecting railroad power lines, multi-echoes properties of laser data and shape knowledge of railroad power lines were employed. Cuboid analysis for detecting seed line segments, tracking lines, connecting and labeling are the main processes. For modeling railroad power lines, iterative RANSAC and least square adjustment were carried out to estimate the lines parameters. The validation of the result is very challenging due to the difficulties in determining the actual references on the ground surface. Standard deviations of 8cm and 5cm for x-y and z coordinates, respectively are satisfactory outcomes. In case of completeness, the result of visual inspection shows that all the lines are detected and modeled well as compare with the original point clouds. The overall processes are fully automated and the methods manage any state of railroad wires efficiently.

A Study Using an Eye-tracker and Cafe Images to Ascertain the Association between the Perception of Spatial Depth and the Customer's Intention to Visit (깊이감과 머물고 싶은 공간의 관계: 시선추적기를 이용한 카페를 중심으로 한 연구)

  • Cho, Ji Young;Kwak, Eun-Ju
    • Science of Emotion and Sensibility
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    • v.22 no.4
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    • pp.3-14
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    • 2019
  • The café has become an important representative "third place" where people study and rest. Hence, it is worthwhile for researchers to understand the needs of individual users as well as the requirements of people who visit such venues in groups. The identification of strategies that can help achieve larger, wider, higher, or deeper interior spaces in small and compact locations can generate benefits for both users and designers. In this study, where 56 interior design students participated, we used an eye-tracker and images of cafes to explore the relationships between spatial depth and the intention to visit a cafe space. The researchers digitally developed fifteen different conditions of space and measured the eye movements of the participants using an eye-tracker when they examined images that appeared to convey the most depth. Participants were also asked to imagine the proposed space images as cafes and to select one of the 15 images as the location that they would be most likely to visit individually and one that they would frequent in the company of other people. The research results revealed that certain ways of using interior design elements altered the participants' perceptions of spatial depth without any change being effected to the actual volume or the size of the space. The participants tended to perceive a space with a small decorative artwork on a dark toned wall with unconnected furniture as deeper than a space with no or large artwork on a light toned wall with contiguous furniture. Spatial depth was a more important consideration for an individual visit than for a group visit. The results of this exploratory study will help scholarly understanding of the role played by spatial depth in customer intentions to visit a cafe.

Development of the Heuristic Attention Model Based on Analysis of Eye Movement of Elementary School Students on Discrimination task (변별과제에서 초등학생의 안구운동 분석을 통한 발견적 주의 모델 개발)

  • Shin, Won-Sub;Shin, Dong-Hoon
    • Journal of The Korean Association For Science Education
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    • v.33 no.7
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    • pp.1471-1485
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    • 2013
  • The purpose of this study was to develop a HAM (Heuristic Attention Model) by analyzing the difference between eye movements according to the science achievement of elementary school students on discrimination task. Science achievement was graded by the results of the Korea national achievement test conducted in 2012 for a random sampling of classes. As an assessment tool to check discrimination task, two discrimination measure problems from TSPS (Test of Science Process Skill, developed in 1994) which were suitable for an eye tracking system were adopted. The subjects of this study were 20 students from the sixth grade who agreed to participate in the research. SMI was used to collect EMD (eye movement data). Experiment 3.2 and BeGaze 3.2 programs were used to plan experiments and analyze EMD. As a result, eye movements of participants in discrimination tasks varied greatly in counts and duration of fixation, first fixation duration, and dwell time, according to students' science achievement and difficulty of the problems. By the analysis of EMD, strategies of the students' problem-solving could be found. During problem solving, subjects' eye movements were affected by visual attention; bottom-up attention, top-down attention and convert attention, and aflunter attention. In conclusion, HAM was developed, and it is believed to help in the development of a science learning program for underachievers.

A Study on IPA-based Competitiveness Enhancement Measures for Regular Freight Service (IPA분석을 이용한 정기화물운송업의 경쟁력 강화방안에 관한 연구)

  • Lee, Young-Jae;Park, Soo-Hong;Sun, Il-Suck
    • Journal of Distribution Science
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    • v.13 no.1
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    • pp.83-91
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    • 2015
  • Purpose - Despite the structural irrationality of multi-level transportation and the oil price rise, the domestic freight transportation market continues to grow, mirroring the rise in e-commerce and resultant increase in courier services and freight volumes. Several studies on courier services have been conducted. However, few studies or statistics have been published regarding regular freight services although they have played a role in the freight service market. The present study identifies the characteristics of regular freight service users to seek competitiveness enhancement measures specific to regular freight services. Research design, data, and methodology - IPA is a comparative analysis of the relative importance of and satisfaction with each attribute simultaneously. This study used IPA because it facilitates the process of analyzing importance and performance, deriving implications and a visual understanding of results. To enhance the competitiveness of regular freight services, this study surveyed its current users regarding the importance of the regular freight service factors. A total of 200 copies of a questionnaire were circulated and 190 copies were returned. In addition to demographics, respondents answered questions about the importance of and satisfaction with services on a 5-point Likert scale. Excluding 3 inappropriate copies, 187 out of 190 copies were analyzed. PASW Statistics 18 was used for statistical analysis. A total of 20 question items were selected for the service factors presented in the questionnaire based on the 1st pilot survey and previous studies. Results - According to the IPA performed to compare the importance of and satisfaction with service factors, both importance and satisfaction are high in the 1st quadrant, which involves the economic advantage of using regular freight services, quick arrival at destinations, weight freight handling, and less time constraints on freight receipt/dispatch. This area requires continuous management. Satisfaction is higher than importance in the 2nd quadrant, which involves the adequacy of freight, cost savings over ordinary courier services, notification on freight arrival, and freight tracking information. This area requires intensive investment and management. Satisfaction is lower than importance in the 3rd quadrant, involving the credit card payment system, courier delivery service, distance to freight handling sites, easy access to freight handling sites, and prompt problem solving. This area requires further intensive management. Both importance and satisfaction are low in the 4th quadrant, involving the availability of collection service, storage space at freight handling sites, kindness of collection/delivery staff, kindness of outlet staff, and easy delivery checks. This area is a set of variables should be excluded from priority control targets. Conclusions - Based on the IPA, service factors that need priority controls because of high importance and low satisfaction include the credit card payment system, delivery service, distance to freight handling sites, easy access to freight handling sites, and prompt problem solving. The findings need to be applied to future marketing strategies for regular freight services and for developing competitiveness enhancement programs.

A Study on the Comparison of the Virtual Reality Development Environment in Unity and Unreal Engine 4 (유니티와 언리얼 엔진 4 에서의 가상현실 개발환경에 관한 비교연구)

  • Yunsik, Cho;Jinmo, Kim
    • Journal of the Korea Computer Graphics Society
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    • v.28 no.5
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    • pp.1-11
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    • 2022
  • Game engines have the advantage of enabling efficient content production, such as reducing development time, with minimal visual quality guarantees and support for multi-platforms. Recently, game engines have provided various functions that can easily, quickly, and effectively produce immersive content using virtual reality (VR) HMD. Therefore, this study conducts a comparative study on the development environment in VR content production using Oculus Quest 2 HMD, focusing on Unity and Unreal game engines, which are widely used in the content production industry, including games. First, we compare the basic setup process of building a development environment using Oculus Quest 2 HMD and a dedicated controller based on a VR template project that includes the minimum functions and settings provided by each engine. Next, we present a simple experience environment that can interact in a virtual environment and compare the development environment to use a dedicated controller and the process of building a development environment that directly utilizes hands through the hand tracking function provided by Oculus Quest 2. Through this process, we will understand the basic process of building a VR development environment, and at the same time, we will check the characteristics and differences of the engine and use it as a research that can be applied to various immersive content production.

Social Network-based Hybrid Collaborative Filtering using Genetic Algorithms (유전자 알고리즘을 활용한 소셜네트워크 기반 하이브리드 협업필터링)

  • Noh, Heeryong;Choi, Seulbi;Ahn, Hyunchul
    • Journal of Intelligence and Information Systems
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    • v.23 no.2
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    • pp.19-38
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    • 2017
  • Collaborative filtering (CF) algorithm has been popularly used for implementing recommender systems. Until now, there have been many prior studies to improve the accuracy of CF. Among them, some recent studies adopt 'hybrid recommendation approach', which enhances the performance of conventional CF by using additional information. In this research, we propose a new hybrid recommender system which fuses CF and the results from the social network analysis on trust and distrust relationship networks among users to enhance prediction accuracy. The proposed algorithm of our study is based on memory-based CF. But, when calculating the similarity between users in CF, our proposed algorithm considers not only the correlation of the users' numeric rating patterns, but also the users' in-degree centrality values derived from trust and distrust relationship networks. In specific, it is designed to amplify the similarity between a target user and his or her neighbor when the neighbor has higher in-degree centrality in the trust relationship network. Also, it attenuates the similarity between a target user and his or her neighbor when the neighbor has higher in-degree centrality in the distrust relationship network. Our proposed algorithm considers four (4) types of user relationships - direct trust, indirect trust, direct distrust, and indirect distrust - in total. And, it uses four adjusting coefficients, which adjusts the level of amplification / attenuation for in-degree centrality values derived from direct / indirect trust and distrust relationship networks. To determine optimal adjusting coefficients, genetic algorithms (GA) has been adopted. Under this background, we named our proposed algorithm as SNACF-GA (Social Network Analysis - based CF using GA). To validate the performance of the SNACF-GA, we used a real-world data set which is called 'Extended Epinions dataset' provided by 'trustlet.org'. It is the data set contains user responses (rating scores and reviews) after purchasing specific items (e.g. car, movie, music, book) as well as trust / distrust relationship information indicating whom to trust or distrust between users. The experimental system was basically developed using Microsoft Visual Basic for Applications (VBA), but we also used UCINET 6 for calculating the in-degree centrality of trust / distrust relationship networks. In addition, we used Palisade Software's Evolver, which is a commercial software implements genetic algorithm. To examine the effectiveness of our proposed system more precisely, we adopted two comparison models. The first comparison model is conventional CF. It only uses users' explicit numeric ratings when calculating the similarities between users. That is, it does not consider trust / distrust relationship between users at all. The second comparison model is SNACF (Social Network Analysis - based CF). SNACF differs from the proposed algorithm SNACF-GA in that it considers only direct trust / distrust relationships. It also does not use GA optimization. The performances of the proposed algorithm and comparison models were evaluated by using average MAE (mean absolute error). Experimental result showed that the optimal adjusting coefficients for direct trust, indirect trust, direct distrust, indirect distrust were 0, 1.4287, 1.5, 0.4615 each. This implies that distrust relationships between users are more important than trust ones in recommender systems. From the perspective of recommendation accuracy, SNACF-GA (Avg. MAE = 0.111943), the proposed algorithm which reflects both direct and indirect trust / distrust relationships information, was found to greatly outperform a conventional CF (Avg. MAE = 0.112638). Also, the algorithm showed better recommendation accuracy than the SNACF (Avg. MAE = 0.112209). To confirm whether these differences are statistically significant or not, we applied paired samples t-test. The results from the paired samples t-test presented that the difference between SNACF-GA and conventional CF was statistical significant at the 1% significance level, and the difference between SNACF-GA and SNACF was statistical significant at the 5%. Our study found that the trust/distrust relationship can be important information for improving performance of recommendation algorithms. Especially, distrust relationship information was found to have a greater impact on the performance improvement of CF. This implies that we need to have more attention on distrust (negative) relationships rather than trust (positive) ones when tracking and managing social relationships between users.