• Journal of Information Processing Systems
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• v.8 no.3
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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.

• Journal of Korea Multimedia Society
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• v.12 no.4
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• pp.492-501
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• 2009

Information on movement of objects in videos can be used as an important part in categorizing and separating the contents of a scene. This paper is proposing a shape-based movement-matching algorithm to effectively find the movement of an object in video streams. Information on object movement is extracted from the object boundaries from the input video frames becoming expressed in continuous 2D shape information while individual 2D shape information is converted into a lD shape feature using the shape descriptor. Object movement in video can be found as simply as searching for a word in a text without a separate movement segmentation process using the sequence of the shape descriptor listed according to order. The performance comparison results with the MPEG-7 shape variation descriptor showed that the proposed method can effectively express the movement information of the object and can be applied to movement search and analysis applications.

• Journal of Korea Multimedia Society
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• v.20 no.7
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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.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.1
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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.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.7
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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.

• Journal of the Ergonomics Society of Korea
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• v.33 no.1
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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.

• Journal of IKEEE
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• v.25 no.3
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• pp.437-444
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• 2021

In this paper, we propose an autonomous driving algorithm that allows a robot to explore various terrains, and implement an application that can monitor the robot's movement path during terrain search. The implemented application consists of a status unit that indicates the position, direction, speed, and motion of the mobile robot, a map unit that displays terrain information obtained through terrain search, and a control unit that controls the movement of the mobile robot. In order to control the movement of the robot, only the start and stop of the search/return is commanded by the application, and all driving for the search is performed autonomously. The basic algorithm for terrain search uses an infrared sensor to check for obstacles in the order of left, front, right, and rear, and if there is no obstacle and the path traveled is a dead end, it returns to the previous position and moves in the other direction to continue the search. Repeat the process to explore the terrain.

• Journal of the Korea Safety Management & Science
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• v.8 no.2
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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.

• Journal of the Ergonomics Society of Korea
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• v.34 no.5
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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.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.10a
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• pp.585-588
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• 2010

The prediction of user location within a building can be applied to many areas like visitor guiding. The existing methods for solving this problem consider limited number of locations a user visited in the past to predict the current location. It cannot model the complex movement patterns, and makes the system inefficient by modeling simple ones too detail. Also it causes prediction errors. In this paper, there is no restriction on the length of past movement patterns to consider for current location prediction. For this purpose, a modified search tree is used. The search tree is constructed to make exact matching as needed for location prediction. The search tree makes the efficient and accurate prediction possible.