• The Journal of the Korea Contents Association
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• v.10 no.10
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• pp.111-119
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• 2010

This paper deals with the experiments of optokinetic differentiation within eye tracking test through the menu direction and cognitive degree of service menu title for watching digital media service. Researcher establish a research topic which verification of differentiations of eye tracking velocity when media user perceive the service menu title within vertical structure or horizontal structure. Experimentation was designed with two types of menu structure-vertical or horizontal-and these have each 9 cases of eye tracking tasks for experimentee. Researcher arrives at a conclusion through as stated above experiment that cases of vertical menu structure is more effective method with linear channel service menu, otherwise that cases of horizontal menu structure is more effective method with non linear channel service menu, like a video on demand service. The research results will be very helpful with actual media industry players when they planning the evolutionary direction of their menu layout.

• Journal of Korea Multimedia Society
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• v.9 no.4
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• pp.470-481
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• 2006

In this paper, we propose a real-time face detection, tracking and tilted face image correction system using multi-color model and face feature information. In the proposed system, we detect face candidate using YCbCr and YIQ color model. And also, we detect face using vertical and horizontal projection method and track people's face using Hausdorff matching method. And also, we correct tilted face with the correction of tilted eye features. The experiments have been performed for 110 test images and shows good performance. Experimental results show that the proposed algorithm robust to detection and tracking of face at real-time with the change of exterior condition and recognition of tilted face. Accordingly face detection and tilted face correction rate displayed 92.27% and 92.70% respectively and proposed algorithm shows 90.0% successive recognition rate.

• The KIPS Transactions:PartB
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• v.13B no.3 s.106
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• pp.283-294
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• 2006

In this paper, we propose a real-time face detection/tracking methodology with Haar wavelets and skin color. The proposed method boosts face detection and face tracking performance by combining skin color and Haar wavelets in an efficient way. The proposed method resolves the problem such as rotation and occlusion due to the characteristic of the condensation algorithm based on sampling despite it uses same features in both detection and tracking. In particular, it can be applied to a variety of applications such as face recognition and facial expression recognition which need an exact position and size of face since it not only keeps track of the position of a face, but also covers the size variation. Our test results show that our method performs well even in a complex background, a scene with varying face orientation and so on.

• Journal of Sensor Science and Technology
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• v.1 no.2
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• pp.155-163
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• 1992

The phased array antenna has the ability to perform adaptive sampling by directing the radar beam without inertia in any direction. The adaptive sampling capability of the phased array antenna allows each sampling time interval to be varied for each target, depending on the acceleration of each target at any time. In this paper we design a three-dimensional adaptive tracking algorithm for the phased array radar system with a given set of measurement parameters. The tracking algorithm avoids taking unnecessarily frequent samples, while keeping the angular prediction error within a fraction of antenna beamwidth so that the probability of detection will not be degraded during a track update illuminations. In our algorithm, the target model and the sampling rate are selected depending on the target range and the target maneuver status which is determined by a maneuver detector. A detailed simulation is conducted to test the validity of our tracking algorithm for encounter geometries under various conditions of maneuver.

• Journal of Internet Computing and Services
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• v.10 no.5
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• pp.13-26
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• 2009

Wireless Sensor Networks (WSNs) is one of the key technologies that make it possible to provide u-service in a ubiquitous society, however, it has disadvantages such as difficulty of managing sensor nodes and weaknesses of stability or mobility in large-scale WSNs. In order to solve these problems, 6LoWPAN that integrates with WSNs and IP networks has been studied widely. In this paper, we propose a Location Tracking Service Based on Google Map (LTSGM) system using 6LoWPAN. Since LTSGM system provides visual location information of sensor nodes through Google Map, it is possible to makes it easier than ever to manage sensor nodes in large-scale WSNs. Moreover, LTSGM can be used for various services such as applications for disaster or crime because it can trace the location of mobile nodes. Implementation of LTSGM system will be a test platform for 6LoWPAN.

• The Journal of the Korea Contents Association
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• v.14 no.9
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• pp.64-75
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• 2014

This study has attempted to explore the audience's visual attention about the subtitles types of CATV entertainment program. To achieve this, this research has measured the dwell time and average fixation data through the eye-tracking test and analysed the reason of particular visual attention by in-depth interview. According to the eye-tracking research findings, four types of subtitles(character metaphor, character metonymy, event metaphor, event metonymy) were measured the highest dwell time and average fixation time. Also, according to in-depth interview, visual attention was clearly turned up that event metonymy constructs the conflicts between characters and overstates the trip place romantically. This results means that staffs of intensify the reality and visual pleasure through event metonymic subtitles.

• The KIPS Transactions:PartB
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• v.10B no.3
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• pp.329-338
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• 2003

Object tracking in a real time image is one of Interesting subjects in computer vision and many practical application fields past couple of years. But sometimes existing systems cannot find object by recognize background noise as object. This paper proposes a method of object detection and tracking using adaptive background image in real time. To detect object which does not influenced by illumination and remove noise in background image, this system generates adaptive background image by real time background image updating. This system detects object using the difference between background image and input image from camera. After setting up MBR(minimum bounding rectangle) using the internal point of detected object, the system tracks object through this MBR. In addition, this paper evaluates the test result about performance of proposed method as compared with existing tracking algorithm.

• Korean Institute of Interior Design Journal
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• v.25 no.3
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• pp.51-59
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• 2016

The technique for Eye-tracking is to trace the movements of pupils so that the eye's exploration response to be digitized. The procedure of Observation Experiment shows a mutual environmental characteristics between men and measuring devices. In order to improve the reliability and to secure the objectivity of the data acquired from eye-tracking, it is very important to analyze the procedures for the experiment to be prepared and the test data to be saved. Based on this viewpoint, the convergent exploration activities at the observation experiment with the objects of sport images were examined to find out what influences the context effect given by experimental environments have on this experiment. In addition, the starting time of attention affecting the reliability of observation data has been estimated. When the observation time is to be subdivided by the unit of second. The attention disperses for the individual characteristics to be appreciated. However, in case of analysis by the overall average, there was the problem that the section of attention dispersed to make it difficult to analyze the subjects' observation features. The study results made it possible to understand the physiological characteristics which were near unconsciousness, when there was an intensive attention for the first 3 seconds and the observation data were shown to be in ordinary range after 4 seconds. The analysis of observation with the focus of the intensive attention enabled the analysis with the first 3 seconds excepted so that it might approach the ordinary range of observation data. The distribution of attention for the first 3 seconds showed the intensive attention, which was on the center. The emergence of intensive attention and the overlapping of the centers can be considered as a context effect due to the correction for the preparing process of experiment. Accordingly, it is thought to be helpful to the security of objectivity and the construction of reliability of eye-tracking data to analyze the observation features shown after the deletion of the data for the first 3 seconds.

• Imaging Science in Dentistry
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• v.52 no.1
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• pp.43-51
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• 2022

Purpose: The aim of this study was to evaluate the reliability of the Vectra M3 (3D Imaging System; Canfield Scientific, Parsippany, NJ, USA) in detecting chin asymmetry, and to assess whether the automatic markerless tracking function is reliable compared to manually plotting landmarks. Materials and Methods: Twenty subjects (18 females and 2 males) with a mean age of 42.5±10.5 years were included. Three-dimensional image acquisition was carried out on all subjects with simulated chin deviation in 4 stages (1-4 mm). The images were analyzed by 2 independent observers through manually plotting landmarks and by Vectra software auto-tracking mode. Repeated-measures analysis of variance and the Tukey post-hoc test were performed to evaluate the differences in mean measurements between the 2 operators and the software for measuring chin deviation in 4 stages. The intraclass correlation coefficient (ICC) was calculated to estimate the intra- and inter-examiner reliability. Results: No significant difference was found between the accuracy of manually plotting landmarks between observers 1 and 2 and the auto-tracking mode (P=0.783 and P=0.999, respectively). The mean difference in detecting the degree of deviation according to the stage was <0.5 mm for all landmarks. Conclusion: The auto-tracking mode could be considered as reliable as manually plotted landmarks in detecting small chin deviations with the Vectra^® M3. The effect on the soft tissue when constructing a known dental movement yielded a small overestimation of the soft tissue movement compared to the dental movement (mean value<0.5 mm), which can be considered clinically non-significant.

• Asia Pacific Journal of Corpus Research
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• v.5 no.1
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• pp.23-36
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• 2024

This research centers on the Taiwan Eye-Movement Corpus of Spanish (TECS), a specially created corpus comprising eye-tracking data from Chinese-speaking learners of Spanish as a third language in Taiwan. Its primary purpose is to explore the broad utility of TECS in understanding language learning processes, particularly the initial stages of language learning. Constructing this corpus involves gathering data on eye-tracking, reading comprehension, and language proficiency to develop a machine-learning model that predicts learner behaviors, and subsequently undergoes a predictability test for validation. The focus is on examining attention in input processing and their relationship to language learning outcomes. The TECS eye-tracking data consists of indicators derived from eye movement recordings while reading Spanish sentences with temporal references. These indicators are obtained from eye movement experiments focusing on tense verbal inflections and temporal adverbs. Chinese expresses tense using aspect markers, lexical references, and contextual cues, differing significantly from inflectional languages like Spanish. Chinese-speaking learners of Spanish face particular challenges in learning verbal morphology and tenses. The data from eye movement experiments were structured into feature vectors, with learner behaviors serving as class labels. After categorizing the collected data, we used two types of machine learning methods for classification and regression: Random Forests and the k-nearest neighbors algorithm (KNN). By leveraging these algorithms, we predicted learner behaviors and conducted performance evaluations to enhance our understanding of the nexus between learner behaviors and language learning process. Future research may further enrich TECS by gathering data from subsequent eye-movement experiments, specifically targeting various Spanish tenses and temporal lexical references during text reading. These endeavors promise to broaden and refine the corpus, advancing our understanding of language processing.