• Journal of Information Processing Systems
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• 제8권3호
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• pp.437-444
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• 2012

In this paper, we propose a method for predicting a user's location based on their past movement patterns. There is no restriction on the length of past movement patterns when using this method to predict the current location. For this purpose, a modified search tree has been devised. The search tree is constructed in an effective manner while it additionally learns the movement patterns of a user one by one. In fact, the time complexity of the learning process for a movement pattern is linear. In this process, the search tree expands to take into consideration more details about the movement patterns when a pattern that conflicts with an existing trained pattern is found. In this manner, the search tree is trained to make an exact matching, as needed, for location prediction. In the experiments, the results showed that this method is highly accurate in comparison with more complex and sophisticated methods. Also, the accuracy deviation of users of this method is significantly lower than for any other methods. This means that this method is highly stable for the variations of behavioral patterns as compared to any other method. Finally, 1.47 locations were considered on average for making a prediction with this method. This shows that the prediction process is very efficient.

• 한국멀티미디어학회논문지
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• 제12권4호
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• pp.492-501
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• 2009

동영상에서 객체의 동작 정보는 장면의 내용을 분류하고 구분하는 중요한 정보로 이용될 수 있다. 본 논문에서는 동영상에서 객체의 동작을 효과적으로 찾기 위한 모양기반 동작 검색 방법을 제안한다. 객체의 동작 정보는 동영상 프레임에서 객체 영역을 추출하여 연속된 2차원 모양 정보로 표현되고, 각각의 2차원 모양 정보는 모양 기술자를 이용하여 1차원 모양 특정값으로 변환된다. 순서에 따라 나열된 모양 기술자 시퀀스를 이용하여 개별 동작의 분할 과정 없이 문서에서 단어를 검색하듯이 동영상에서 객체의 동작을 검색할 수 있다. MPEG-7 모양 변화 기술자와의 성능 비교 실험을 통하여 제안된 방법이 객체의 동작 정보를 보다 효과적으로 표현할 수 있으며, 동작 검색 및 분석 응용에 적용할 수 있음을 보였다.

• 한국멀티미디어학회논문지
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• 제20권7호
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• pp.986-993
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• 2017

Object Tracking is a technique for tracking moving objects over time in a video image. Using object tracking technique, many research are conducted such a detecting dangerous situation and recognizing the movement of nearby objects in a smart car. However, it still remains a challenging task such as occlusion, deformation, background clutter, illumination variation, etc. In this paper, we propose a novel deep visual object tracking method that can be operated in robust to many challenging task. For the robust visual object tracking, we proposed a Convolutional Neural Network(CNN) which shares weight of the convolutional layers. Input of the CNN is a three; first frame object image, object image in a previous frame, and current search frame containing the object movement. Also we propose a method to consider the motion of the object when determining the current search area to search for the location of the object. Extensive experimental results on a authorized resource database showed that the proposed method outperformed than the conventional methods.

• 한국정보통신학회논문지
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• 제25권1호
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• pp.160-163
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• 2021

In this paper, we present a path search scheme for the safe movement of the swarm of unmanned systems in unknown dangerous areas. Some of the swarm searches for the primary and secondary paths before the majority of swarm move through dangerous areas. In terms of rapid movement from the dangerous area and preparation for an accident, the primary path is searched first in the destination's direction. The secondary path is searched by considering the distance between the paths to guarantee a safe distance. The computer simulations show that the proposed scheme is suitable for the swarm of unmanned systems.

• 제어로봇시스템학회논문지
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• 제18권7호
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• pp.673-679
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• 2012

This paper introduces robust tracking algorithm for fast and erratic moving object. CAMSHIFT algorithm has less computation and efficient performance for object tracking. However, the method fails to track a object if it moves out of search window by fast velocity and/or large movement. The size of the search window in CAMSHIFT algorithm should be selected manually also. To solve these problems, we propose an efficient prediction technique for fast movement of object using Kalman Filter with automatic initial setting and variable configuration technique for search window. The proposed method is compared to the traditional CAMSHIFT algorithm for searching and tracking performance of objects on test image frames.

• 대한인간공학회지
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• 제33권1호
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• pp.69-76
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• 2014

Objective: This study aims to present literature providing researchers with insights on specific fields of research and highlighting the major issues in the research topics. A systematic review is suggested using content analysis on literatures regarding "visual search", "eye movement", and "eye track". Background: Literature review can be classified as "narrative" or "systematic" depending on its approach in structuring the content of the research. Narrative review is a traditional approach that describes the current state of a study field and discusses relevant topics. However, since literatures on specific area cover a broad range, reviewers inherently give subjective weight on specific issues. On the contrary, systematic review applies explicit structured methodology to observe the study trends quantitatively. Method: We collected meta-data of journal papers using three search keywords: visual search, eye movement, and eye track. The collected information contains an unstructured data set including many natural languages which compose titles and abstracts, while the keyword of the journal paper is the only structured one. Based on the collected terms, seven categories were evaluated by inductive categorization and quantitative analysis from the chronological trend of the research area. Results: Unstructured information contains heavier content on "stimuli" and "condition" categories as compared with structured information. Studies on visual search cover a wide range of cognitive area whereas studies on eye movement and eye track are closely related to the physiological aspect. In addition, experimental studies show an increasing trend as opposed to the theoretical studies. Conclusion: By systematic review, we could quantitatively identify the characteristic of the research keyword which presented specific research topics. We also found out that the structured information was more suitable to observe the aim of the research. Chronological analysis on the structured keyword data showed that studies on "physical eye movement" and "cognitive process" were jointly studied in increasing fashion. Application: While conventional narrative literature reviews were largely dependent on authors' instinct, quantitative approach enabled more objective and macroscopic views. Moreover, the characteristics of information type were specified by comparing unstructured and structured information. Systematic literature review also could be used to support the authors' instinct in narrative literature reviews.

• 전기전자학회논문지
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• 제25권3호
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• pp.437-444
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• 2021

본 논문은 로봇이 다양한 지형 탐색이 가능한 자율 주행 알고리즘을 제안하고, 지형 탐색 중 로봇의 이동 경로를 모니터링 할 수 있는 애플리케이션을 구현한다. 구현한 애플리케이션은 이동 로봇의 위치, 방향, 속력, 동작을 나타내는 상태부와 지형 탐색을 통해 얻은 지형 정보를 나타내는 지도부, 이동 로봇의 동작을 제어하는 제어부로 구성된다. 로봇의 움직임 제어는 탐색/복귀의 시작과 정지만 애플리케이션으로 명령하고, 탐색을 위한 모든 주행은 자율로 하도록 하였다. 지형 탐색의 기본적인 알고리즘은 적외선 센서를 이용해 좌측, 전방, 우측, 후방 순으로 장애물을 확인하여 장애물이 없는 곳이 이동하고 이동한 경로가 막다른 길이면 이전 위치로 돌아와 다른 방향으로 이동하여 탐색을 계속하는 과정을 반복하여 지형을 탐색한다.

• 대한안전경영과학회지
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• 제8권2호
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• pp.71-80
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• 2006

There are many display panels in the flight cockpit and pilots get various flight information from those displays. The ergonomic layout of the displays must be determined based upon frequency of use and sequence of use. This study investigated the visual search patterns of the six display groups(one head-up-display: HUD, two multi function displays: MFDs, one engine group: EG, one flight display group: FD and others) in a fighting aircraft. Four expert pilots conducted Imaginary flight in the physical mock-up and the eye movements were collected using eye tracking system. Data of dwell time, frequency of use, and eye movement path were collected. Pilots spent most of time on HUD(55.2%), and others (21.6%), FD(14.2%), right MFD(4.7%), EG(3.2%), and left MFD(1.1%) in descending order. Similarly HUD(42.8%) and others(30.0%) were the most frequently visited displays. These data can be used in the layout of cockpit displays and the determination of optimal visual search pattern.

• 대한인간공학회지
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• 제34권5호
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• pp.377-399
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• 2015

Objective: The aim of this study is to understand and identify the critical issues in vision research area using content analysis and network analysis. Background: Vision, the most influential factor in information processing, has been studied in a wide range of area. As studies on vision are dispersed across a broad area of research and the number of published researches is ever increasing, a bibliometric analysis towards literature would assist researchers in understanding and identifying critical issues in their research. Method: In this study, content and network analysis were applied on the meta-data of literatures collected using three search keywords: 'visual search', 'eye movement', and 'eye tracking'. Results: Content analysis focuses on extracting meaningful information from the text, deducting seven categories of research area; 'stimuli and task', 'condition', 'measures', 'participants', 'eye movement behavior', 'biological system', and 'cognitive process'. Network analysis extracts relational aspect of research areas, presenting characteristics of sub-groups identified by community detection algorithm. Conclusion: Using these methods, studies on vision were quantitatively analyzed and the results helped understand the overall relation between concepts and keywords. Application: The results of this study suggests that the use of content and network analysis helps identifying not only trends of specific research areas but also the relational aspects of each research issue while minimizing researchers' bias. Moreover, the investigated structural relationship would help identify the interrelated subjects from a macroscopic view.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2010년도 추계학술대회
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• pp.585-588
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• 2010

건물 내에서 특정 사용자의 현 위치를 예측하는 문제는 방문자의 안내 등 다양하게 응용될 수 있다. 이 문제를 풀기 위해 기존 방법들은 사용자가 과거에 이동한 패턴을 한정된 길이만큼만 고려하여 예측한다. 이는 복잡한 이동 패턴을 모델링 할 수 없고, 단순한 이동 패턴은 필요 이상으로 상세히 모델링함으로써 시스템의 효율을 떨어뜨림은 물론이고, 예측 오류를 야기한다. 본 논문에서는 기존의 방법들과는 달리 최근 이동 경로의 길이에 제한을 두지 않고 이동 패턴을 구분하는데 필요한 만큼만 고려하여 예측 결과를 도출하고자 한다. 이를 위해 탐색 트리를 사용하는데, 이 탐색 트리는 위치 예측에 필요한 만큼만 장소를 비교하도록 구성된다. 이 탐색 트리는 효율적이고 정확한 예측을 가능하게 해준다.