• 한국멀티미디어학회논문지
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• 제14권8호
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• pp.992-999
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• 2011

This paper proposed a human body posture recognition program based on haar-like feature and hand activity detection. Its distinguishing features are the combination of face detection and motion detection. Firstly, the program uses the haar-like feature face detection to receive the location of human face. The haar-like feature is provided with the advantages of speed. It means the less amount of calculation the haar-like feature can exclude a large number of interference, and it can discriminate human face more accurately, and achieve the face position. Then the program uses the frame subtraction to achieve the position of human body motion. This method is provided with good performance of the motion detection. Afterwards, the program recognises the human body motion by calculating the relationship of the face position with the position of human body motion contour. By the test, we know that the recognition rate of this algorithm is more than 92%. The results show that, this algorithm can achieve the result quickly, and guarantee the exactitude of the result.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2003년도 ISIS 2003
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• pp.399-402
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• 2003

This paper deals with the making avatar like a caricature from human face image which is made by web camera. Generally, the Image made by web camera is not low quality but also, there are always various lights and backgrounds. So, It is impossible to recognize a human face's contour by some methods which only find some feature points of a image. Therefore, In this paper, we propose a new method for overcoming defeat of that methods. First, we got the area of human face roughly by color information. And then, we could find the exact human face's contour by using B-spline Snake.

• 로봇학회논문지
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• 제3권4호
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• pp.270-277
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• 2008

The development of a face robot basically targets very natural human-robot interaction (HRI), especially emotional interaction. So does a face robot introduced in this paper, named Buddy. Since Buddy was developed for a mobile service robot, it doesn't have a living-being like face such as human's or animal's, but a typically robot-like face with hard skin, which maybe suitable for mass production. Besides, its structure and mechanism should be simple and its production cost also should be low enough. This paper introduces the mechanisms and functions of mobile face robot named Buddy which can take on natural and precise facial expressions and make dynamic gestures driven by one laptop PC. Buddy also can perform lip-sync, eye-contact, face-tracking for lifelike interaction. By adopting a customized emotional reaction decision model, Buddy can create own personality, emotion and motive using various sensor data input. Based on this model, Buddy can interact probably with users and perform real-time learning using personality factors. The interaction performance of Buddy is successfully demonstrated by experiments and simulations.

• 제어로봇시스템학회논문지
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• 제11권1호
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• pp.50-57
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• 2005

We present a simple and effective method of face and facial feature detection under pose variation of user face in complex background for the human-robot interaction. Our approach is a flexible method that can be performed in both color and gray facial image and is also feasible for detecting facial features in quasi real-time. Based on the characteristics of the intensity of neighborhood area of facial features, new directional template for facial feature is defined. From applying this template to input facial image, novel edge-like blob map (EBM) with multiple intensity strengths is constructed. Regardless of color information of input image, using this map and conditions for facial characteristics, we show that the locations of face and its features - i.e., two eyes and a mouth-can be successfully estimated. Without the information of facial area boundary, final candidate face region is determined by both obtained locations of facial features and weighted correlation values with standard facial templates. Experimental results from many color images and well-known gray level face database images authorize the usefulness of proposed algorithm.

• 융합신호처리학회논문지
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• 제12권4호
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• pp.228-236
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• 2011

Emotion recognition plays an important role in the research area of human-computer interaction, and it allows a more natural and more human-like communication between humans and computer. Most of previous work on emotion recognition focused on extracting emotions from face, speech or EEG information separately. Therefore, a novel approach is presented in this paper, including face, speech and EEG, to recognize the human emotion. The individual matching scores obtained from face, speech, and EEG are combined using a weighted-summation operation, and the fused-score is utilized to classify the human emotion. In the experiment results, the proposed approach gives an improvement of more than 18.64% when compared to the most successful unimodal approach, and also provides better performance compared to approaches integrating two modalities each other. From these results, we confirmed that the proposed approach achieved a significant performance improvement and the proposed method was very effective.

• Asia pacific journal of information systems
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• 제34권2호
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• pp.585-619
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• 2024

This paper delves into the comparative analysis of human interactions with AI agents based on the presence or absence of a facial representation, combined with the presence or absence of paralanguage voice elements. The "CASA (Computer-Are-Social-Actors)" paradigm posits that people perceive computers as social actors, not tools, unconsciously applying human norms and behaviors to computers. Paralanguages are speech voice elements such as pitch, tone, stress, pause, duration, speed that help to convey what a speaker is trying to communicate. The focus is on understanding how these elements collectively contribute to the generation of flow, intimacy, trust, and interactional enjoyment within the user experience. Subsequently, this study uses PLS analysis to explore the connections among all variables within the research framework. This paper has academic and practical implications.

• 한국산업정보학회논문지
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• 제17권3호
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• pp.1-7
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• 2012

개인 정보가 중요한 사용자 증명 수단으로서 활용됨에 따라 신뢰 할 수 있는 인증수단이 요구 되면서 최근에는 사람의 신체 일부를 비밀 번호처럼 사용하는 생체 인식 시스템에 대한 연구가 많이 시도되고 있다. 개인 얼굴의 특징을 이용하는 얼굴 인식 기술은 특징점 추출이 용이하여 많이 활용되고 있다. 본 논문에서는 무선접수 인터페이스를 위한 얼굴인식 시스템을 구현하였다. 제안된 시스템은 사용자 인증 을 위해 크게 얼굴 검출과 얼굴 인식으로 나누고 있다. 먼저 피부색 색상 정보와 Haar-like feature를 이용하여 얼굴을 추출한다. 다음 으로 얼굴 인식을 위해 PCA와 LDA를 조합하는 방법을 사용한다. 개발된 시스템을 이용하여 무인접수 인터페이스에 적용 가능함을 보였다.

• 디지털융복합연구
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• 제11권9호
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• pp.311-318
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• 2013

얼굴 검출 기법들의 경우 조명과 배경에 따라 검출의 정확도가 떨어지는 현상이 발생하여, 이를 해결하기 위한 기법들이 요구되고 있다. 본 연구에서는 얼굴의 눈과 입의 성분을 분석하여 인간의 감성 정보를 추출하기 위한 데이터를 획득하고자 한다. 이를 위해 처리속도가 빠르고 환경 요소들에 강인한 검출율을 보이는 얼굴 특징 검출 방법을 제안하였다. 본 방법은 적분 이미지를 적용한 Haar-like Feature기법을 이용하여 얼굴 성분(두 눈, 입)을 검출한 후, 색상 정보를 바탕으로 검출된 성분들을 이진화하고 피부영역과 얼굴 성분영역을 구분한다. 그 후, 빠르고 정확한 shape를 생성하기 위해 베지어 곡선을 이용하여 검출된 성분들의 shape를 생성한다. 제안된 방법의 성능을 평가하기 위하여 Face Recognition Homepage의 데이터를 이용하여 실험을 진행하였으며, 이를 통해 정교한 얼굴 성분 검출이 가능함을 확인하였다.

• 디지털산업정보학회논문지
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• 제8권1호
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• pp.29-40
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• 2012

A challenging research issue that has been one of growing importance to those working in human-computer interaction are to endow a machine with an emotional intelligence. Thus, emotion recognition technology plays an important role in the research area of human-computer interaction, and it allows a more natural and more human-like communication between human and computer. In this paper, we propose the multimodal emotion recognition system using face and speech to improve recognition performance. The distance measurement of the face-based emotion recognition is calculated by 2D-PCA of MCS-LBP image and nearest neighbor classifier, and also the likelihood measurement is obtained by Gaussian mixture model algorithm based on pitch and mel-frequency cepstral coefficient features in speech-based emotion recognition. The individual matching scores obtained from face and speech are combined using a weighted-summation operation, and the fused-score is utilized to classify the human emotion. Through experimental results, the proposed method exhibits improved recognition accuracy of about 11.25% to 19.75% when compared to the most uni-modal approach. From these results, we confirmed that the proposed approach achieved a significant performance improvement and the proposed method was very effective.

• 한국생활과학회지
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• 제14권5호
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• pp.813-820
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• 2005

The beauty itself cannot be changed by the time, but the concept of the beauty can be influence by the time and cultural background. The purpose of this study is to analyze the beautiful faces or ugly faces among the young women and to provide useful guideline to make up for the modem concept of beauty. The facial photographs of 180 adlut women(aged between 20 and 29) in Pusan and Ulsan area were sampled to be measured and classified as the beautiful or ordinary or ugly faces. Data were analyzed by Frequencies, Mean, Duncan's Multiple Range Test. The major results were as followings; the Beautiful face has a relatively small face with a broad forehead and a small lower face. It also has a wide palpebral fissure, narrow intercanthal distance, a narrow nose and a big mouth. Physiognomic face length was 182.38mm, the upper face length was 59.82mm, the middle face length 60.82mm, the lower face length 61.76mm, and the index of face length to face breadth was 1.35. And also the faces within the figures are considered as the beautiful or ordinary or ugly faces from those measurements like face length/bizygion breadth, intercanthal distance, mouth width, upper vermilion height, lower vermilion height.