• Journal of Institute of Control, Robotics and Systems
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• v.4 no.1
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• pp.82-87
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• 1998

In this study, the theoretical resolution analysis of an active vision system using laser range finder is performed for surrounding recognition and 3D data acquisition in unknown environment. In the result, the resolution of range data in laser range finder is depend on the distance between lens center of CCD camera and light emitter, view angle, beam angle, and parameters of CCD camera. The theoretical resolutions of the laser range finders of various types which are based on parameters effected resolution are calculated and experimental results are obtained in real system.

• The Journal of Korea Robotics Society
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• v.3 no.2
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• pp.99-105
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• 2008

To achieve autonomous mobile robot navigation, accurate localization technique is the fundamental issue that should be addressed. In augmented reality, the position of a user is required for location-based services. This paper presents indoor localization using infrared reflective artificial landmarks. In order to minimize the disturbance to the user and to provide the ease of installation, the passive landmarks are used. The landmarks are made of coated film which reflects the infrared light efficiently. Infrared light is not visible, but the camera can capture the reflected infrared light. Once the artificial landmark is identified, the camera's relative position/orientation is estimated with respect to the landmark. In order to reduce the number of the required artificial landmarks for a given environment, the pan/tilt mechanism is developed together with the distortion correction algorithm.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.341-343
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• 1995

In this paper, an algorithm is presented to recogniz the driving direction of a vehicle and obstacles in front of it based on highway road image. The algorithm employs a neural network with 27 sub sets obtained from the road image as its input. The outputs include the direction of the vehicle movement and presence or absence of obstacles. The road image, obtained by a video camera, was digitized and processed by a personal computer equipped with an image processing board.

• Proceedings of the IEEK Conference
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• 2007.07a
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• pp.231-232
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• 2007

This paper introduce a new touchless fingerprint sensor. Two mirrors are used to capture the side fingerprint images which cannot detectable using a single camera. We also propose the techniques which can solve the image contrast, nonuniform illumination, DOF(Depth of Field) problems. This new sensor leads to bringing new challenges in the field of fingerprint recognition.

• Annual Conference of KIPS
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• 2020.11a
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• pp.1022-1024
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• 2020

본 논문에서는 구면 영상을 사용한 vSLAM에 의해 생성된 환경 지도에서 실내 공간을 인식하는 방법을 제안한다. 환경 지도는 오픈 소스 라이브러리 OpenVSLAM을 사용하여 생성했다. 카메라 방향과 위치를 기준으로 랜드 마크를 분류하고 허프 변환을 사용해서 실내 공간의 각 벽의 위치를 찾아냈다. 실험 결과 추정된 평면들이 실제 벽면과 유사한 위치에 나타남을 알 수 있었다. 제시하는 알고리즘은 현재의 AR 콘텐츠보다 진보된 AR 콘텐츠를 제작하는 데 사용할 수 있다.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.333-335
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• 2015

A computer vision-based scene recognition algorithm is proposed for monitoring construction sites. The system analyzes images acquired from a surveillance camera to separate regions and classify them as building, ground, and hole. Mean shift image segmentation algorithm is tested for separating meaningful regions of construction site images. The system would benefit current monitoring practices in that information extracted from images could embrace an environmental context.

• Annual Conference of KIPS
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• 2007.11a
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• pp.50-54
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• 2007

우리 삶에서 빼놓을 수 없는 기기인 휴대폰의 다양한 컨텐츠 기술 개발의 필요하다. 이러한 필요성을 충족하기 위하여 휴대폰에서 얻은 저 품질 악보 영상을 인식하는 기능을 구현하고 MIDI화일로 저장된 악보를 연주하는 시스템을 제안한다. 휴대폰 카메라를 통하여 얻은 영상을 인식한 결과 평균 93.4%의 악보 인식률을 얻을 수 있었다.

• ETRI Journal
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• v.37 no.2
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• pp.395-405
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• 2015

We address the problem of uncooperative person recognition through continuous monitoring. Multiple modalities, such as face, height, clothes color, and voice, can be used when attempting to recognize a person. In general, not all modalities are available for a given frame; furthermore, only some modalities will be useful as some frames in a video sequence are of a quality that is too low to be able to recognize a person. We propose a method that makes use of stochastic information updates of temporal modalities and environment estimators to improve person recognition performance. The environment estimators provide information on whether a given modality is reliable enough to be used in a particular instance; such indicators mean that we can easily identify and eliminate meaningless data, thus increasing the overall efficiency of the method. Our proposed method was tested using movie clips acquired under an unconstrained environment that included a wide variation of scale and rotation; illumination changes; uncontrolled distances from a camera to users (varying from 0.5 m to 5 m); and natural views of the human body with various types of noise. In this real and challenging scenario, our proposed method resulted in an outstanding performance.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.5
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• pp.143-150
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• 2017

In this paper, we propose a novel motion recognition platform using smart-phone tracking and color communication. The interface requires only a camera and a personal smart-phone to provide a motion control interface rather than expensive equipment. The platform recognizes the user's gestures by the tracking 3D distance and the rotation angle of the smart-phone, which acts essentially as a motion controller in the user's hand. Also, a color coded communication method using RGB color combinations is included within the interface. Users can conveniently send or receive any text data through this function, and the data can be transferred continuously even while the user is performing gestures. We present the result that implementation of viable contents based on the proposed motion recognition platform.

• Journal of Korea Multimedia Society
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• v.17 no.4
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• pp.506-513
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• 2014

In recent years, research on user's activity recognition using a smart phone has attracted a lot of attentions. A smart phone has various sensors, such as camera, GPS, accelerometer, audio, etc. In addition, smart phones are carried by many people throughout the day. Therefore, we can collect log data from smart phone sensors. The log data can be used to analyze user activities. This paper proposes an approach to inferring a user's physical activities based on the tri-axis accelerometer of smart phone. We propose recognition method for four activity which is physical activity; sitting, standing, walking, running. We have to convert accelerometer raw data so that we can extract features to categorize activities. This paper introduces a recognition method that is able to high detection accuracy for physical activity modes. Using the method, we developed an application system to recognize the user's physical activity mode in real-time. As a result, we obtained accuracy of over 80%.