• Proceedings of the Korean Information Science Society Conference
• /
• 2011.06c
• /
• pp.358-361
• /
• 2011

본 논문에서는 요주의 인물 식별 시스템에 직접적으로 적용이 가능한 실용적 차원의 정면 얼굴 탐지 시스템을 제안한다. 제안된 시스템은 개선된 피부색 탐지기를 통해 실시간으로 입력되는 영상의 이미지로부터 얼굴 탐지 범위를 축소하고, Viola 등의 단계형 분류기를 통해 얼굴 여부를 빠른 속도로 탐지함으로써 실시간 탐지가 가능케 하였다. 또한, 마스킹을 통하여 비 정면 얼굴들을 제거함으로써 정면 얼굴만을 보다 정확하게 탐지할 수 있으며, 정면 얼굴 데이터만으로 학습된 SVDD로 최종 출력을 검증하였다. 공인된 벤치마킹 데이터인 FEI Face Database을 사용하여 제안한 SVDD 기반의 정면 얼굴 탐지 시스템의 성능을 실험적으로 평가한다.

• Proceedings of the Korean Society of Computer Information Conference
• /
• 2019.01a
• /
• pp.243-246
• /
• 2019

본 논문에서는 감성과 힐링, 머신러닝이라는 주제를 바탕으로 딥러닝을 통한 사용자의 얼굴표정을 인식하고 그 얼굴표정을 기반으로 음악을 재생해주는 얼굴표정 기반의 음악재생 프로그램을 제안한다. 얼굴표정 기반 음악재생 프로그램은 딥러닝 기반의 음악 프로그램으로써, 이미지 인식 분야에서 뛰어난 성능을 보여주고 있는 CNN 모델을 기반으로 얼굴의 표정을 인식할 수 있도록 데이터 학습을 진행하였고, 학습된 모델을 이용하여 웹캠으로부터 사용자의 얼굴표정을 인식하는 것을 통해 사용자의 감정을 추측해낸다. 그 후, 해당 감정에 맞게 감정을 더 증폭시켜줄 수 있도록, 감정과 매칭되는 노래를 재생해주고, 이를 통해, 사용자의 감정이 힐링 및 완화될 수 있도록 도움을 준다.

• Proceedings of the Korean Information Science Society Conference
• /
• 2001.10b
• /
• pp.460-462
• /
• 2001

컴퓨터 이미지처리는 여러 분야에서 응용되고 있는데 어떤 특성을 만족하는 객체들의 계수를 자동으로 분류시키는 생물학분야, 편지봉투나 일반양식에 인쇄되어 있는 글자를 자동으로 검출하고 인식하며 초음파검사 혹은 X-Ray 촬영에서 이미지를 획득하여 향상시키는 의료분야, 지문 및 얼굴인식 등에 이용되고 있다. 최근 몇 년 동안 이미지인식, 형태론, 이미지데이터 압축에 관한 연구가 진전되면서 본 연구에서 형태론적인 기법을 사용하여 문자인식을 위한 전처리 혹은 후처리 단계에서 사용되는 이미지향상을 위해서 팽창, 침식, 골격화의 3단계를 적용하고 기존의 연구 방법과 비교하여 이미지획득 시간을 줄이고 이미지를 향상시켰다.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.47 no.2
• /
• pp.33-44
• /
• 2010

This paper propose the structure of real-time face detection hardware architecture for robot vision processing applications. The proposed architecture is robust against illumination changes and operates at no less than 60 frames per second. It uses Modified Census Transform to obtain face characteristics robust against illumination changes. And the AdaBoost algorithm is adopted to learn and generate the characteristics of the face data, and finally detected the face using this data. This paper describes the face detection hardware structure composed of Memory Interface, Image Scaler, MCT Generator, Candidate Detector, Confidence Comparator, Position Resizer, Data Grouper, and Detected Result Display, and verification Result of Hardware Implementation with using Virtex5 LX330 FPGA of Xilinx. Verification result with using the images from a camera showed that maximum 32 faces per one frame can be detected at the speed of maximum 149 frame per second.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.19 no.1
• /
• pp.1-5
• /
• 2009

This paper suggests to apply mirror-reflected method based 2D emotion recognition database to 3D application. Also, it makes facial expression of fuzzy modeling using probability of emotion. Suggested facial expression function applies fuzzy theory to 3 basic movement for facial expressions. This method applies 3D application to feature vector for emotion recognition from 2D application using mirror-reflected multi-image. Thus, we can have model based on fuzzy nonlinear facial expression of a 2D model for a real model. We use average values about probability of 6 basic expressions such as happy, sad, disgust, angry, surprise and fear. Furthermore, dynimic facial expressions are made via fuzzy modelling. This paper compares and analyzes feature vectors of real model with 3D human-like avatar.

• Journal of Korea Multimedia Society
• /
• v.12 no.8
• /
• pp.1128-1141
• /
• 2009

Graphical expressions are continuously improving, spurred by the astonishing growth of the game technology industry. Despite such improvements, users are still demanding a more natural gaming environment and true reflections of human emotions. In real life, people can read a person's moods from facial color and expression. Hence, interactive facial colors in game characters provide a deeper level of reality. In this paper we propose a facial color adaptive technique, which is a combination of an emotional model based on human emotion theory, emotional expression pattern using colors of animation contents, and emotional reaction speed function based on human personality theory, as opposed to past methods that expressed emotion through blood flow, pulse, or skin temperature. Experiments show this of expression of the Facial Color Model based on facial color adoptive technique and expression of the animation contents is effective in conveying character emotions. Moreover, the proposed Facial Color Adaptive Technique can be applied not only to 2D games, but to 3D games as well.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.50 no.1
• /
• pp.225-231
• /
• 2013

In this study, we propose the design of optimized pRBFNNs-based night vision face recognition system using PCA algorithm. It is difficalt to obtain images using CCD camera due to low brightness under surround condition without lighting. The quality of the images distorted by low illuminance is improved by using night vision camera and histogram equalization. Ada-Boost algorithm also is used for the detection of face image between face and non-face image area. The dimension of the obtained image data is reduced to low dimension using PCA method. Also we introduce the pRBFNNs as recognition module. The proposed pRBFNNs consists of three functional modules such as the condition part, the conclusion part, and the inference part. In the condition part of fuzzy rules, input space is partitioned by using Fuzzy C-Means clustering. In the conclusion part of rules, the connection weights of pRBFNNs is represented as three kinds of polynomials such as linear, quadratic, and modified quadratic. The essential design parameters of the networks are optimized by means of Differential Evolution.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.15 no.1
• /
• pp.110-115
• /
• 2005

This paper proposes the method to detect contours of a face, eyes and a mouth in a color image for making an avatar automatically. First, we use the HSI color model to exclude the effect of various light condition, and we find skin regions in an input image by using the skin color is defined on HS-plane. And then, we use deformable templates and Genetic Algorithm(GA) to detect contours of a face, eyes and a mouth. Deformable templates consist of B-spline curves and control point vectors. Those can represent various shape of a face, eyes and a mouth. And GA is very useful search procedure based on the mechanics of natural selection and natural genetics. Second, an avatar is created automatically by using contours and Fuzzy C-means clustering(FCM). FCM is used to reduce the number of face color As a result, we could create avatars like handmade caricatures which can represent the user's identity, differing from ones generated by the existing methods.

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

• 한국HCI학회:학술대회논문집
• /
• 2007.02a
• /
• pp.761-766
• /
• 2007

이 논문에서는 커널 Edge Map 방식의 얼굴의 특징점을 검출하는 방법과 Adaboost를 이용한 얼굴의 특징점을 검출하는 방법을 이용하여 좀 더 강인한 얼굴의 특징점을 검출해 낸다. 커널 Edge Map을 이용한 방법은 기존의 10개의 커널을 이용하여 검출된 Edge를 이용하지 않고 좀 더 빠르게 검출해내기 위해 2개의 커널을 이용하여 얼굴의 특징점을 검출해 낸다. 이렇게 만들어진 얼굴의 특징점 후보군들에서 Adaboost를 이용하여 좀 더 정확하고 빠른 특징점을 찾을 수 있게 된다. Adaboost를 이용한 방법은 각각의 특징점들을 오프라인 상에서 학습을 하고 실시간으로 특징점을 검출하는 방법을 사용하였다. Edge를 이용한 방법으로 이미지의 전처리를 하여 후보군을 찾고 그 후보군과 Adaboost를 이용한 후보군들의 조합으로 인해 좀 더 강인하게 얼굴의 특징점을 찾을 수 있다.