• Proceedings of the Korea Information Processing Society Conference
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• 2016.10a
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• pp.566-567
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• 2016

최근 스마트기기가 발전함에 따라 종이책이 아닌 다양한 전자책뷰어가 등장하고 있다. 애플의 아이패드(iPad), 아마존의 킨들(kindle)과 같은 태블릿, 전자책 또는 스마트폰이 대표적인 예이며 스마트기기의 사용자 증가로 전용 단말기가 아닌 스마트폰 중심의 전자책 시장도 크게 성장하고 있다. 하지만 시니어 또는 스마트기기 사용을 어려워하는 사용자들이 전자책을 사용하는데 어려움을 느끼기 때문에, 전자책은 종이책에 비해 여전히 낮은 이용률을 나타내고 있다. 본 논문에서는 얼굴 표정에 따라서 전자책 설정을 자동으로 변경해 주는 방법을 제안한다. 제안한 방법은 표정감지를 위하여 OpenCV 라이브러리를 이용하여 얼굴을 검출하고, Haar-Like 피처 기법으로 사용자의 눈 모양을 검출한다. 눈이 감겨있는 경우와 찌푸린 경우를 감지하여 이에 맞게 글자크기와 화면을 자동으로 설정해 준다.

• Journal of Information Technology Services
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• v.6 no.3
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• pp.241-249
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• 2007

This paper describes a real-time face tracking system using effective detector and Kalman filter. In the proposed system, an image is separated into a background and an object using a real-time updated face color for effective face detection. The face features are extracted using the five types of simple Haar-like features. The extracted features are reinterpreted using Principal Component Analysis (PCA), and interpreted principal components are used for Support Vector Machine (SVM) that classifies the faces and non-faces. The moving face is traced with Kalman filter, which uses the static information of the detected faces and the dynamic information of changes between previous and current frames. The proposed system sets up an initial skin color and updates a region of a skin color through a moving skin color in a real time. It is possible to remove a background which has a similar color with a skin through updating a skin color in a real time. Also, as reducing a potential-face region using a skin color, the performance is increased up to 50% when comparing to the case of extracting features from a whole region.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.8
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• pp.5263-5268
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• 2014

This paper suggests a fast human detection algorithm that can be applied to a high-resolution CCTV camera. Human detection algorithms, which used a HOG detector show high performance in the region of image processing. On the other hand, it is difficult to apply to real-time high resolution imaging because of its slow processing speed in the extracting figures of HOG. To resolve this problems, we suggest how to detect humans into two stages. First, candidates of a human region are found using background subtraction, and humans and non-humans are distinguished using a HOG detector only. This process increases the detection speed by approximately 2.5 times without any degradation in performance.

• Proceedings of the Korean Information Science Society Conference
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• 2011.06c
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• pp.405-408
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• 2011

In this paper, we propose a robot remote control system based on mouth tracking. The main idea behind the work is to help disabled people who cannot operate a joystick or keyboard to control a robot with their hands. The mouth detection method in this paper is mainly based on the Adaboost feature detection approach. By using the proposed new Haar-like features for detecting the corner of mouth, the speed and accuracy of detection are improved. Combined with the Kalman filter, a continuous and accurate mouth tracking has been achieved. Meanwhile, the gripping commands of the robot manipulator were also achieved by the recognition of the user.s mouth shape, such as 'pout mouth' or 'grin mouth'. To assess the validity of the method, a mouth detection experiment and a robot cargo transport experiment were applied. The result indicated that the system can realize a quick and accurate mouse tracking; and the operation of the robot worked successfully in moving and bringing back items.

• The KIPS Transactions:PartA
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• v.13A no.7 s.104
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• pp.639-646
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• 2006

Data compression technologies enable us to store and transfer large amount of data efficiently, and become more and more important due to increasing data size and the network traffic. Moreover, as a result of the increase of computing power, volumetric data produced from various applied science and engineering fields has been getting much larger. In this Paper, we present a volume compression scheme which exploits Daubeches wavelet transform. The proposed scheme basically supports lossy compression for 3D volume data, and provides unit-wise random accessibility. Since our scheme shows far lower error rates than the previous compression methods based on Haar filter, it could be used well for interactive visualization applications as well as large volume data compression requiring image fidelity.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.3
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• pp.229-235
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• 2011

To make a robust object tracking and identifying system for an intelligent robot and/or home system, heterogeneous sensor fusion between visible ray system and infrared ray system is proposed. The proposed system separates the object by combining the ROI (Region of Interest) estimated from two different images based on a heterogeneous sensor that consolidates the ordinary CCD camera and the IR (Infrared) camera. Human's body and face are detected in both images by using different algorithms, such as histogram, optical-flow, skin-color model and Haar model. Also the pose of human body is estimated from the result of body detection in IR image by using PCA algorithm along with AdaBoost algorithm. Then, the results from each detection algorithm are fused to extract the best detection result. To verify the heterogeneous sensor fusion system, few experiments were done in various environments. From the experimental results, the system seems to have good tracking and identification performance regardless of the environmental changes. The application area of the proposed system is not limited to robot or home system but the surveillance system and military system.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2014.10a
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• pp.245-246
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• 2014

This paper suggests the navigation information display system which is based on augmented reality technology and especially focuses on image analysis technology. Navigator has to always confirm the information from marine electronic navigation devices and then they compare with the view of outside targets of the windows. During this 'head down' posture, they feel uncomfortable and sometimes it cause near-accidents such as collision or missing objects, because he or she cannot keep an eye on the front view of windows. Augmented reality can display both of information of virtual and real in a single display. Therefore we tried to adapt the AR technology to help navigators and have been studied and developed image pre-processing module as a previous research already. To analysis the outside view of the bridge window, we have extracted navigational information from the camera image by using image processing. This paper mainly describes about recognizing ship feature by haar-like feature and filtering region of interest area by AIS data, which are to improve accuracy of the image analysis.

• Proceedings of the Korea Information Processing Society Conference
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• 2000.10b
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• pp.887-890
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• 2000

본 연구에서는 내용기반 영상 데이터 검색을 위하여 변환 영역에서 위치 정보와 주파수 정보를 가지는 웨이블릿 성질을 이용하여 영상을 압축한 후에 저주파 성분에 의한 객체들의 특징을 추출하는 방안으로 Vector Quantization 을 이용한 class 별 영상 검색을 제시한다 내용기반 영상 검색의 주요특징들은 색상, 질감, 그리고 영상의 공간적인 특징을 고려한 특징 값 둥이 사용된다. 먼저 검색의 효율성을 높이기 위해 영상을 구성하는 특징 치 중에서 가장 빈도가 많은 class 부터 영상의 유사도를 검색한 후에 다음으로 영상을 구성하는 빈도가 큰 순서대로 DB 내에 저장되어 있는 영상과 비교를 하게 된다. DB내 영상 검색은 빈도수가 우선인 5개의 class를 기준으로 유사도를 측정해서 검색을 이룬다. 이러한 영상의 특징들을 어떻게 결합하고 특징 추출을 하느냐에 따라 검색의 효율성에 영향을 준다. 따라서 본 연구에서는 영상의 위치 정보와 주파수 정보를 가지는 웨이블릿 변환 후 얻어지는 저대역 부밴드에서의 공간적인 특성을 고려한 특징 값을 이용하여 Vector Quantization 알고리즘에 의해 정지영상의 객체 대표 특징들을 마르게 검색하고자 한다. 본 연구에서는 Haar Wavelet과 Vector Quantization 에서 색상과 질감의 가중치를 적용한 후 DB 에 저장된 영상과 유사도를 검색하는 방법을 취하고자 한다.

• Journal of Convergence Society for SMB
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• v.3 no.1
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• pp.31-41
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• 2013

There have been various recent methods proposed in detecting driver drowsiness (DD) to avert fatal accidents. This work proposes a hardware/software (HW/SW) co-design approach in implementation of a DD detection system adapted from an AdaBoost-based object detection algorithm with Haar-like features [1] to monitor driver's eye closure rate. In this work, critical functions of the DD detection algorithm is accelerated through custom hardware components in order to speed up processing, while the software component implements the overall control and logical operations to achieve the complete functionality required of the DD detection algorithm. The HW/SW architecture was implemented on an Altera DE2 board with a video daughter board. Performance of the proposed implementation was evaluated and benchmarked against some recent works.

• Journal of IKEEE
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• v.16 no.4
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• pp.375-381
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• 2012

In this paper, we present an implementation of Viola-Jones algorithm in a multi-core SoC by using skin color information and a parallel processing method. In order to reduce unnecessary operations and improve the detection speed, we adopted a face detection algorithm based on skin color and deleted background image. The algorithm is functionally divided into several parts taking account of the size and the dependency so that the divided functions can be proceeded in parallel. Experiment results in SoC with built-in Cortex-A9 multi core show that it is about 1.8 times faster than the existing algorithm which is not divided.