• Journal of the Korea Academia-Industrial cooperation Society
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• v.8 no.2
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• pp.240-244
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• 2007

Non-intrusive methods based on active remote IR illumination fur eye tracking is important for many applications of vision-based man-machine interaction. One problem that has plagued those methods is their sensitivity to lighting condition change. This tends to significantly limit their scope of application. In this paper, we present a new real-time eye detection and tracking methodology that works under variable and realistic lighting conditions. Based on combining the bright-pupil effect resulted from IR light and the conventional appearance-based object recognition technique, our method can robustly track eyes when the pupils are not very bright due to significant external illumination interferences. The appearance model is incorporated in both eyes detection and tracking via the use of support vector machine and the mean shift tracking. Additional improvement is achieved from modifying the image acquisition apparatus including the illuminator and the camera.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.13 no.3
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• pp.206-211
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• 2020

It is Face recognition is a very important process in image monitoring and it is a form of biometric technology. The recognition process involves many variables and is highly complex, so the software development has only begun recently with the development of hardware. Face detection technology using the CCTV is a process that precedes face analysis, and it is a technique that detects where the face is in the image. Research in face detection and recognition has been difficult because the human face reacts sensitively to different environmental conditions, such as lighting, color of skin, direction, angle and facial expression. The utility and importance of face recognition technology is coming into the limelight over time, but many aspects are being overlooked in the facial area detection technology that must precede face recognition. The system in this paper can detect tilted faces that cannot be detected by the AdaBoost detector and It could also be used to detect other objects.

• Journal of Life Science
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• v.25 no.10
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• pp.1124-1131
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• 2015

Consumer interest in the stability of medicinal herb extracts during storage has increased. Although the advent of new technologies has improved preservation conditions, increasing the storage time, there are few studies on the preservation of herb extracts. The purpose of this study was to perform microscopic observations of Samul-tang decoctions under various preservation conditions. The storage temperature (a high temperature, room temperature, with or without light, refrigeration, or cryopreservation) and storage time (0, 15, 30, 90, and 180 days) were given to each condition Macroscopic morphology, pH, UV absorption, HPLC, and bacteriological studies were performed to determine microscopic changes in Samul-tang decoctions. The biological activity (tyrosinase inhibition) of the Samul-tang decoctions was also examined. There were no major changes in the indicated observation items when the extracts were stored in each condition. However, at higher storage temperatures and longer storage times, microscopic changes increased, although no bacteria were detected. Furthermore, the higher the storage temperature was and the longer the storage time was, the bigger the change was, despite of minor microscopic changes. Therefore, to maintain the stability of herbal extracts during storage, it is recommended to keep the Samul-tang decoction in the preservation condition of refrigeration and cryopreservation or without light rather than high temperature and room temperature as possible.

• Journal of Internet of Things and Convergence
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• v.5 no.1
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• pp.7-11
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• 2019

This study suggests a methodology to track crime suspects or anomalies through CCTV in order to expand the scope of CCTV use as the number of CCTV installations continues to increase nationwide in recent years. For the abnormal behavior classification, we use the existing studies to find out suspected criminals or abnormal actors, use CNN to track objects, and connect the surrounding CCTVs to each other to predict the movement path of objectified objects CCTVs in the vicinity of the path were used to share objects' sample data to track objects and to track objects. Through this research, we will keep track of criminals who can not be traced, contribute to the national security, and continue to study them so that more diverse technologies can be applied to CCTV.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2016.11a
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• pp.146-147
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• 2016

손동작 인식은 대부분 스킨 컬러 검출을 이용하였다. 하지만 이와 같은 방법으로는 빛이나 주변 사물에 의해 영향을 많이 받기 때문에 정확한 값을 일정하게 도출 해낼 수 없었다. 이에 본 논문은 운동축적 기법을 이용하여 움직임을 파악한 후 손의 움직임을 트랙킹하여 운동 방향을 구한다. 제안된 시스템은 C/C++을 기반으로 구현하여, 실험에서 제안 방법이 안정적이고 우수한 성능을 보여줌을 증명하였다.

• The Journal of the Korea institute of electronic communication sciences
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• v.12 no.5
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• pp.859-864
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• 2017

IoT is a new emerging technology to lead the $4^{th}$ industry renovation and has been widely used in industry and home to increase the quality of human being. In this paper, IoT based face detection and recognition system for a smart elevator is developed. Haar cascade classifier is used in a face detection system and a proposed PCA algorithm written in Python in the face recognition system is implemented to reduce the execution time and calculates the eigenfaces. SVM or Euclidean metric is used to recognize the faces detected in the face detection system. The proposed system runs on RaspberryPi 3. 200 sample images in ORL face database are used for training and 200 samples for testing. The simulation results show that the recognition rate is over 93% for PP+EU and over 96% for PP+SVM. The execution times of the proposed PCA and the conventional PCA are 0.11sec and 1.1sec respectively, so the proposed PCA is much faster than the conventional one. The proposed system can be suitable for an elevator monitoring system, real time home security system, etc.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.423-425
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• 2019

Users may experience a sub-type of motion sickness, called cybersickness, when interacting with virtual reality (VR) applications in the state of wearing head mounted display (HMD) devices. Although the root cause of cybersickness is still unclear, it is believed to result from a sensory mismatch between visual and vestibular systems. However, there is a lack of studies developing data collection and analysis systems to measure cybersickness. In this paper, therefore, a system is designed that collects electroencephalography (EEG) and physiological data from a user wearing a VR HMD device through an internet of things (IoT) platform and decides whether a user experiences a symptom of cybersickness, namely dizziness, or not by using a decision threshold. Experimental results showed that the proposed system achieved about 92% accuracy of a dizziness detection when considering 14 participants.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2003.10a
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• pp.227-232
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• 2003

Non-intrusive methods based on active remote IR illumination for eye tracking is important for many applications of vision-based man-machine interaction. One problem that has plagued those methods is their sensitivity to lighting condition change. This tends to significantly limit their scope of application. In this paper, we present a new real-time eye detection and tracking methodology that works under variable and realistic lighting conditions. eased on combining the bright-pupil effect resulted from IR light and the conventional appearance-based object recognition technique, our method can robustly track eyes when the pupils are not very bright due to significant external illumination interferences. The appearance model is incorporated in both eyes detection and tracking via the use of support vector machine and the mean shift tracking. Additional improvement is achieved from modifying the image acquisition apparatus including the illuminator and the camera.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.10a
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• pp.894-897
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• 2012

We propose a effective method using the HOG (Histogram of Oriented Gradients) feature vector to track individual objects in an environment which multiple objects are moving. The proposed algorithm consists of pre-processing, object detection and object tracking. We experimented with six videos which have various trajectories and the movement. When occlusion between objects was occurred, we identified individual object by using center and predicted coordinates of moving objects. The algorithm shows 85.45% of tracking rate in the videos we experimented. We expect the proposed system is utilized in security systems which require the alalysis of the position and motion pattern of objects.

• KIPS Transactions on Computer and Communication Systems
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• v.9 no.6
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• pp.137-142
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• 2020

As research on security systems using IoT (Internet of Things) devices increases, the need for research to track the location of specific objects is increasing. The goal is to detect the movement of objects in real-time and to predict the radius of movement in short time. Many studies have been done to clearly recognize and detect moving objects. However, it does not require the sharing of information between cameras that recognize objects. In this paper, using the device information of the camera and the video information taken from the camera, the movement radius of the object is predicted and information is shared about the camera within the radius to provide the movement path of the object.