• Journal of Broadcast Engineering
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• v.25 no.6
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• pp.944-953
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• 2020

Object detection plays a crucial role in a self-driving system. With the advances of image recognition based on deep convolutional neural networks, researches on object detection have been actively explored. In this paper, we proposed a lightweight model of the mask R-CNN, which has been most widely used for object detection, to efficiently predict location and shape of various objects on the road environment. Furthermore, feature maps are adaptively re-calibrated to improve the detection performance by applying an attention module to the neural network layer that plays different roles within the mask R-CNN. Various experimental results for real driving scenes demonstrate that the proposed method is able to maintain the high detection performance with significantly reduced network parameters.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.13 no.6
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• pp.496-502
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• 2020

The electronic attendance management system is being introduced and operated on a pilot basis by some universities and educational institutions. However, most of the related systems have installed and operated the existing barcode and magnetic card systems. Classroom attendance is managed by introducing RF cards, but it causes problems such as recognition distance (less than 5cm) and the need for a check process in which students have to read the card each time with a reader for attendance. Also, it is not possible to respond in real time to the situation of midterm (early leave, absence from the second lecture time, etc.) because it is used in the lecture time of one subject with the record checked once. In order to solve these problems, the various mobile attendance systems proposed to solve these problems are also unable to fundamentally solve problems such as interim attendance and proxy attendance because they check attendance using only the application of a smartphone. In this paper, we use geofencing technology, which is a positioning-based technology that detects the entry and exit of people, objects, etc. in areas separated by virtual boundaries. The proposed system solves the problem of intermediate attendance and alternate attendance by setting the student to automatically record the access record when entering and leaving the classroom set as a geofence with a smartphone. In addition, it also provides a function to prevent unintentional mistakes that occur through the smartphone by limiting some of the functions of the smartphone such as silence, vibration, and Internet use when entering the classroom.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.2
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• pp.63-70
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• 2022

Although 2D Object detection has been largely improved in the past years with the advance of deep learning methods and the use of large labeled image datasets, 3D object detection from 2D imagery is a challenging problem in a variety of applications such as robotics, due to the lack of data and diversity of appearances and shapes of objects within a category. Google has just announced the launch of Objectron that has a novel data pipeline using mobile augmented reality session data. However, it also is corresponding to 2D-driven 3D object detection technique. This study explores more mature 2D object detection method, and applies its 2D projection to Objectron 3D lifting system. Most object detection methods use bounding boxes to encode and represent the object shape and location. In this work, we explore a stochastic representation of object regions using Gaussian distributions. We also present a similarity measure for the Gaussian distributions based on the Hellinger Distance, which can be viewed as a stochastic Intersection-over-Union. Our experimental results show that the proposed Gaussian representations are closer to annotated segmentation masks in available datasets. Thus, less accuracy problem that is one of several limitations of Objectron can be relaxed.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.6
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• pp.63-72
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• 2017

This study made of centrally actual application in general arts classes based on movie in university. Especially, I analyzed the activities of the class with 'Untouchable: 1% friendship' among 6 films. The objects of this study are 44 students of D university in Busan Metropolitan City who take 'creative fusion from movie' general arts class which opened first semester in 2016. In this study, students were able to watch movies through the creative class, which was out of the traditional classroom method, and after 15 hours of learning the quiz online, they conducted 15 weeks as a teaching method to perform tasks, presentations, experiments, and experiences in regular class time. The results of this study are as follows. 'It is a general arts class that makes movements live,' 'It is a general arts class that shows movies from various perspectives,' and 'It is a general arts class that makes me know.' This suggests that the educational medium, which is easily accessible in everyday life, and the general arts class, which is active in the space outside the framework, are perceived as stimulating curiosity and adding fun to college students.

• Journal of Internet Computing and Services
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• v.24 no.5
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• pp.29-35
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• 2023

CCTV is used for various purposes such as crime prevention, public safety reinforcement, and traffic management. However, as the range and resolution of the camera improve, there is a risk of exposing personal information in the video. Therefore, there is a need for new technologies that can identify individuals while protecting personal information in images. In this paper, we propose histogram-based singular value decomposition for object identification and tracking. The proposed method distinguishes different objects present in the image using color information of the object. For object recognition, YOLO and DeepSORT are used to detect and extract people present in the image. Color values are extracted with a black-and-white histogram using location information of the detected person. Singular value decomposition is used to extract and use only meaningful information among the extracted color values. When using singular value decomposition, the accuracy of object color extraction is increased by using the average of the upper singular value in the result. Color information extracted using singular value decomposition is compared with colors present in other images, and the same person present in different images is detected. Euclidean distance is used for color information comparison, and Top-N is used for accuracy evaluation. As a result of the evaluation, when detecting the same person using a black-and-white histogram and singular value decomposition, it recorded a maximum of 100% to a minimum of 74%.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.23 no.2
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• pp.69-78
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• 2024

Recently, the use of CCTV to prevent crowd accidents has been promoted, but research is needed to compensate for the spatial limitations of CCTV. In this study, pedestrian density was measured using drone footage, and based on a review of existing literature, a threshold of 6.7 people/m² was selected as the cutoff risk level for crowd accidents. In addition, we conducted a preliminary study to determine drone parameters and found that the pedestrian recognition rate was high at a drone altitude of 20 meters and an angle of 60°. Based on a previous study, we selected a target area with a high concentration of pedestrians and measured pedestrian density, which was found to be 0.27~0.30 per m². The study shows it is possible to measure risk levels by determining pedestrian densities in target areas using drone images. We believe drone surveillance will be utilized for crowd safety management in the near future.

• Journal of Internet Computing and Services
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• v.25 no.1
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• pp.29-37
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• 2024

In this paper, we propose an efficient image processing system to detect and track the movement of specific objects such as patients. The proposed system extracts the outline area of an object from a binarized difference image by applying a thinning algorithm that enables more precise detection compared to previous algorithms and is advantageous for mixed-mode design. The binarization and thinning steps, which require a lot of computation, are designed based on RTL (Register Transfer Level) and replaced with optimized hardware blocks through logic circuit synthesis. The designed binarization and thinning block was synthesized into a logic circuit using the standard 180n CMOS library and its operation was verified through simulation. To compare software-based performance, performance analysis of binary and thinning operations was also performed by applying sample images with 640 × 360 resolution in a 32-bit FPGA embedded system environment. As a result of verification, it was confirmed that the mixed-mode design can improve the processing speed by 93.8% in the binary and thinning stages compared to the previous software-only processing speed. The proposed mixed-mode system for object recognition is expected to be able to efficiently monitor patient movements even in an edge computing environment where artificial intelligence networks are not applied.

• Journal of the Korean Society for information Management
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• v.41 no.1
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• pp.261-282
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• 2024

This study proposed and evaluated electroencephalography (EEG)-based and eye-tracking-based methods to determine relevance by utilizing users' implicit relevance feedback while navigating content in a digital library. For this, EEG/eye-tracking experiments were conducted on 32 participants using video, image, and text data. To assess the usefulness of the proposed methods, deep learning-based artificial intelligence (AI) techniques were used as a competitive benchmark. The evaluation results showed that EEG component-based methods (av_P600 and f_P3b components) demonstrated high classification accuracy in selecting relevant videos and images (faces/emotions). In contrast, AI-based methods, specifically object recognition and natural language processing, showed high classification accuracy for selecting images (objects) and texts (newspaper articles). Finally, guidelines for implementing a digital library interface based on EEG, eye-tracking, and artificial intelligence technologies have been proposed. Specifically, a system model based on implicit relevance feedback has been presented. Moreover, to enhance classification accuracy, methods suitable for each media type have been suggested, including EEG-based, eye-tracking-based, and AI-based approaches.

• Korean Journal of Psychosomatic Medicine
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• v.4 no.2
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• pp.170-181
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• 1996

Objective : This study was tried to investigate the specific relationships among cognitve function, neurbehavioral symptoms, and daily living functions, as well as provide the guidline of more proper clinical approches for patients with subcortical cerebrovascular disease. Objects and Methods Subjects were 85 patients whose diagnosis was confirmed by brain CT or MRI and controls were 195 normal persons matched by educational level with the subjects. The cognitive functions were evaluated by BNA(Benton neuropsychiatric assessment), subjective neurobehavioral symptoms by SCL-90-R(Sympton Check List-90-Revised), objective neurobehavioral symptoms by NRS(Neurobehavioral Rating Scale), and daily living function symptoms by NRS(Neurobehavioral Rating Scale), and daily living function by GERRI(Geriatric Evaluation by Relative's Rating Instrument) and IADL(Instrumental Activities of Daily Living Scale). Results: 1) Subjects showed significantly lower cognitive functions than controls in all tests of BNA except Lt-Rt Orientation Test(p=0.09) and facial Recognition Test(p=0.186). 2) In subjective neurobehavioral symptoms, subjects showed significantly lower scores in all symptoms except anxiety(p=0.059), hostility(p=0.159), and phobic anxiety(p=0.849). But in objects neurobehavioral symptoms, subjects showed significantly higher in scores in psychoticism (p=0.000) and neuroticism(p=0.025) of NRS. 3) The score of social functioning of GERRI(p=0.000) and that of IADL(p=0.000) were significantly higher in subjects than in controls. 4) for correlation between cognitive and daily living functions, there were significant correlations between the scores of all items on BNA and the score of cognitive or social function of GERRI and the socre of MDL in corntrols, whereas in subjects, there were significant correlations only between the scores of BNA and the score of IADL. 5) for correlation between neuroehavioral symptoms and daily living functions, there were significant correlatons between the socre of subjective neurobehavioral symptoms and the scores of all subscales of GERRI and the score of MDL in controls. On the contrary, in subjects, there were significant correlations between the score of social function of GERRI and the score of objective neurobehavioral symptoms such as psychoticism, agitiation-hostility, and decrease d motivation-emotional withdrawl. Conclusion : Above results suggest that disturbances in specific function of brain may play a role as a predictor of impairments with specific daily living functions and also suggest that specific correlations among various functions may be useful as clinical parameters for setting of the treatment goal and for assessing the ongoing process in the treatment and rehavilitation of the patients with subcortical cerebrovascular disease.

• Korean Journal of Health Education and Promotion
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• v.9 no.1
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• pp.1-13
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• 1992

The purpose of this thesis is to provide the framework of the health education curriculum on a school level which should be accomplishe in futrue and farthermore to establish the health education as a independent and regular course. The relation among the status in quo and the satisfaction degree of health education, the degree of the knowledge about health, the degree of the understanding of the health education and the degree of requirement for the health education curriculum has been analyzed in this paper. The research has been carried out through the questionnaire forms distributed to the girl students and the instructors at a few general senior high school and vocational senior high schools in Seoul, and the consequences are as follows : 1. As to the degree of understanding of the health education, it has been indicated that the health education should be performed one or two hours a week from the elementary school for all the boy and girl students by the experts trained in the departments concerned with health. 2. Concerning the degree of requirement for health education curriculum, the high school girl students have shown the need for first aid, sex education, environmental health, drinking, smoking, drug abuse, maternal and child health, industrial health, safety health, mental health, growth & development, epidemiology, the old health in the order named. On the other hand, the instructors have shown the need for drinking, smoking, drug abuse, sex education, maternal and child health, public health and industrial health also in the order named. The items having low degree of requirement are biostatistics, community health and health administration in case of the gril students and biostatistics, health administration and health economics in case of the instructors. 3. The status in quo and the satisfaction degree of the health education has proved higher in senior high school curriculums than in junior high school curriculums, and the most instructive course about health has turned out to be gymnastics in junior high school and the training course in senior high school respectively. 4. As to the degree of understanding of the health education in case of the girl students, the significance has been found between the health condition and the time for performing the health education, the monthly income and the objects for the health education, and the school records and the school hours per week. The significance has been shown only in regard to the school records in case of the degree of requriement for the health education curriculum. 5. The degree of requirement for the health education in case of the instructors has shown the significance between the teching career and the need for the health education. In addition, the degree of requirement for the health education curriculum has indicated significance with regard to sex and age. 6. The degress of the understanding of the health education according to the degree of knowledge about health and the degree of requirement for the health educatio curriculum have been all turned out to be statistically significant. 8. Among the factors which have an influence on the degree of the understanding of the health education, the recognition of the relation between the health course and the training course has significatly influenced the selection of the health education instructors. In additon, the understanding of the need for the health eduation has significantly influenced the objects for the instructors and the school hours, and the understanding of the need for establishing the health education course has significatly influenced the time for performing the health education.