• Journal of IKEEE
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• v.18 no.1
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• pp.106-113
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• 2014

A pedestrian detector can be applied for various purposes such as monitoring or counting the number of people in some place, or detecting the people plunging in the driveway. There was a lot of related research. But, the detection speed is slow in embedded system because of the limited computing power. An algorithm for fast pedestrian detector using HOG in ARM SIMD architecture is presented in this paper. There is a way to quickly remove the background of image and to improve the detection speed using NEON parallel technique. When we tested with INRIA Person Dataset, the proposed pedestrian detector improves the speed by 3.01 times than previous one.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.11
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• pp.2486-2491
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• 2013

There are invisible defects by naked eyes in ceramic material images such as internal stomata, cracks and foreign substances. In this paper we propose a method to detect and extract such defects from ceramic pipe weld zone by applying ART2 learning. In pre-processing, we apply Ends-in Search Stretching to enhance the intensity and then perform fuzzy binarization with triangle type membership function followed by enhanced ART2 that interacts with random input patterns to extract such invisible defects. The experiment verifies that this proposed method is sufficiently effective.

• Journal of the Korea Society of Computer and Information
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• v.14 no.4
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• pp.47-57
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• 2009

Event detection and recognition is an active and challenging topic recent in Computer Vision. This paper describes a new method for recognizing events caused by human motion from video sequences in an office environment. The proposed approach analyzes human motions using Motion History Image (MHI) sequences, and is invariant to body shapes. types or colors of clothes and positions of target objects. The proposed method has two advantages; one is thant the proposed method is less sensitive to illumination changes comparing with the method using color information of objects of interest, and the other is scale invariance comparing with the method using a prior knowledge like appearances or shapes of objects of interest. Combined with edge detection, geometrical characteristics of the human shape in the MHI sequences are considered as the features. An advantage of the proposed method is that the event detection framework is easy to extend by inserting the descriptions of events. In addition, the proposed method is the core technology for event detection systems based on context-aware computing as well as surveillance systems based on computer vision techniques.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.9
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• pp.119-128
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• 2014

In this paper, a fast human detection method using adaptive UV-histogram and template matching is proposed. The proposed method improves the detection rate in the scene of complex environment. The method firstly generates U-histogram to extract human candidates and adaptively generates V-histogram for each labled U-histogram, thus it could extract humans correctly, which was impossible in the previous method. The method tries to match the human candidates with the adaptively sized omega shape template to the focal length and distance in order to improve the detection accuracy. It also detects false positives by rematching the template with accumulated foreground images and hence is robust to the occlusion. Experimental results showed that the proposed method has superior performance to the Bae's method in the complex environment with about 15% improvement in precision and 80% in recall and has 20 times faster processing time than Xia's method.

• Analytical Science and Technology
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• v.17 no.3
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• pp.211-216
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• 2004

Commercial one-step rapid fecal occult blood (FOB) kit which was used as a screening test to detect traces of blood in stool samples was evaluated for the feasibility of the forensic identification of human blood. The sensitivity was determined and compared with the conventional Leucomalichite green (LMG) method. In addition, the specificity of the kit and the effects of various chemicals and environmental factors were examined. FOB kit was specific for human hemoglobin and more sensitive than LMG test (approximately 100 times). FOB kit showed positive band using at least 1,000,000-fold diluted human blood. The antigen was very stable regardless of storage temperature and boiling. The positive reaction was not affected by LMG and Luminol, the traditional tests for identification of bloodstain. As a results, FOB test kit could be effectively applied to identification of human blood at crime scene and crime laboratories.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.413-415
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• 2019

In this paper, we develop IoT-HiAS(IoT-Human Interactive Advertising Service) for sharing economy. The HiAS device shooting the front of the device via a webcam and recognizes the person in real time through the SSD model using MobileNet. If the number of persons above the set threshold is recognized by counting the recognized person, the advertisement is reproduced on the idle resource through the beam projector. At the same time as the advertisement is reproduced, the captured image of the advertisement start time in the front of the device and the number of recognized persons are sends the IoT server of an oneM2M-compliant HiAS server using the IoT client. When the advertisement is finish, the webcam is shooting the front of the device and the image is sends the IoT server. We implemented the IoT-based human interactive advertising service by transmitting the received data to the advertiser and the advertising producers through the SNS(Social Network Service) agent of the HiAS server.

• Journal of Korea Multimedia Society
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• v.4 no.6
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• pp.510-517
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• 2001

In this paper, we implement a real time speaker close-up system using lip motion information from input images having some people. After detecting a speaker from input moving pictures through one color CCD camera, the other camera closes up the speaker by using lip motion information. The implemented system detects a face and lip area of each person by means of a facial color and a morphological information, and then finds out a speaker by using lip area variation. A PTZ(Pan/Tilt/Zoom) camera is used in order to close up the detected speaker and it is controlled by RS-232C serial port. Consequently, we can exactly detect a speaker in input moving pictures including more than three people.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38C no.7
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• pp.643-649
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• 2013

In this paper, human heartbeat detection using signal reflected from the antenna which is varied reflection coefficient by near field variation of the antenna. For detection reflected signal from antenna, 20 dB directional coupler is used because of not affecting transmitting signal. Variance of reflection coefficient of dipole antenna is about 0.07 dB which is too small the distinction between heartbeat and noise. Sensitivity increasing method is applied and heartbeat is clearly detected. Due to phase and magnitude errors come from discrete value components, antenna is located some points in experiments ro find optimum sensitivity position. And providing verification of using communication signal, heartbeat detection when frequency modulated signal which have 4 MHz bandwidth is applied.

• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.654-658
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• 2008

은행에서 현금 지급기(ATM)를 부정한 목적으로 사용하는 사람들은 보통 마스크나 선글라스, 모자 같은 것으로 얼굴을 은폐하고 인출을 하는 경우가 많다. 그렇기 때문에 마스크나 선글라스, 모자로 얼굴을 가림으로써 특징을 검출하기 쉽지 않아 얼굴 인식을 통한 사람 판단이 어렵다. 본 논문에서는 차 영상과 Template Matching 을 통해 얼굴 영역을 추출하고 Adaptive Boost 를 통해 얼굴의 특징 점을 검출한 후 스킨 컬러 정보를 이용하여 현재 사람의 은폐 정보를 추정하는 방법을 제안한다. 제안된 방영은 영상신호처리에 강하고 비용이 적으며 적은 전력으로 동작하는 DSP 기반에 탑재 함으로써 ATM 기에 탑재하기 적합하고 또한 다른 형태의 검증 시스템에 적용할 수 있는 효율적인 구조를 제시한다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2011.07a
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• pp.430-431
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• 2011

본 논문에서는 카메라 내장형 텔레비전을 통해 획득한 영상을 이용한 간단한 체조 게임을 제안한다. 팔을 수평 방향으로 벌리는 과정을 간단한 체조 게임이라고 정의한다. 이를 위해 첫 번째 단계로 연속적으로 입력되는 영상의 평균 영상을 통하여 배경 영상으로 정의한다. 두 번째 단계로 배경 영상과의 차이를 이용한 사람 영역을 검출한다. 세 번째 단계로 검출된 사람 영역에 대해 세로 방향 축의 사영을 통해 특징 벡터를 구한다. 마지막 단계로 특징 벡터를 SVM(Support Vector Machine)을 이용해 학습 및 분류를 수행하여 간단한 체조 게임 인식을 위한 사람의 움직임을 구분하는 방법을 제안한다.