• Journal of Information Processing Systems
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• 제5권2호
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• pp.41-68
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• 2009

Face recognition presents a challenging problem in the field of image analysis and computer vision, and as such has received a great deal of attention over the last few years because of its many applications in various domains. Face recognition techniques can be broadly divided into three categories based on the face data acquisition methodology: methods that operate on intensity images; those that deal with video sequences; and those that require other sensory data such as 3D information or infra-red imagery. In this paper, an overview of some of the well-known methods in each of these categories is provided and some of the benefits and drawbacks of the schemes mentioned therein are examined. Furthermore, a discussion outlining the incentive for using face recognition, the applications of this technology, and some of the difficulties plaguing current systems with regard to this task has also been provided. This paper also mentions some of the most recent algorithms developed for this purpose and attempts to give an idea of the state of the art of face recognition technology.

• 정보처리학회논문지B
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• 제16B권5호
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• pp.385-394
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• 2009

사람의 얼굴은 강체(Rigid object)가 아니기 때문에 얼굴을 추적하거나 인식하는 일은 쉽지 않다. 특히 얼굴의 포즈나 주변 조명의 변화에 따른 입력 영상의 차이는 얼굴 인식을 어렵게 하는 주된 원인이다. 본 논문에서는 비디오 영상으로부터 얼굴을 추적하고 인식할 때 발생하는 이 두 가지의 문제를 해결하기 위한 프레임웍과 전처리 방법을 제안한다. 얼굴 포즈의 변화에도 효과적으로 얼굴을 추적 및 인식하기 위해 먼저 학습 영상으로부터 주성분 분석법(Principal Component Analysis)을 이용하여 각 얼굴 포즈마다 하나의 독립된 가우시안 분포를 추정하고 이를 이용하여 각 사람마다 가우시안 혼합 모델(Gaussian Mixture Model)을 구성한다. 본 논문에서는 서로 다른 조명 상태를 가진 얼굴 영상을 처리하기 위해 먼저 입력된 얼굴 영상을 SSR(Single Scale Retinex) 모델을 이용하여 반사율(Reflectance)과 조도(Illuminance)로 분해한다. 반사율은 사전 정의된 범위 안에서 히스토그램 평활화를 수행함으로써 재조정되고 조도는 조명의 변화를 포함하고 있지 않은 영상들으로부터 학습된 매니폴드 모델로 다시 근사된다. 이 두 특징을 결합함으로써 실내 환경이나 실외 환경에서 촬영된 영상에서 효율적으로 얼굴을 추적 및 인식한다. 비디오 기반의 영상으로부터 보다 효율적으로 얼굴을 추적하기 위해 본 논문에서는 구성된 모델의 가중치를 각 프레임마다 이전 프레임의 추적 결과에 의해 EM 알고리즘을 이용하여 갱신함으로써 비디오 영상내의 연속적으로 변화하는 얼굴 포즈를 추정하였다. 본 논문에서 제안된 방법은 실내에서의 다양한 조명환경과 실외의 여러 장소에서 획득한 실험 영상을 이용하여 기존에 연구되어 온 다른 방법에 비해 우수한 성능을 보였다.

• Journal of information and communication convergence engineering
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• 제21권4호
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• pp.287-293
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• 2023

With the rapid development of domestic and international over-the-top markets, a large amount of video content is being created. As the volume of video content increases, consumers tend to increasingly check data concerning the videos before watching them. To address this demand, video summaries in the form of plot descriptions, thumbnails, posters, and other formats are provided to consumers. This study proposes an approach that automatically generates posters to effectively convey video content while reducing the cost of video summarization. In the automatic generation of posters, face recognition and clustering are used to gather and classify character data, and keyframes from the video are extracted to learn the overall atmosphere of the video. This study used the facial data of the characters and keyframes as training data and employed technologies such as DreamBooth, a text-to-image generation model, to automatically generate video posters. This process significantly reduces the time and cost of video-poster production.

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송공학회 2010년도 하계학술대회
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• pp.42-45
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• 2010

This paper proposes an intelligent video surveillance system for human object tracking. The proposed system integrates the object extraction, human object recognition, face detection, and camera control. First, the object in the video signals is extracted using the background subtraction. Then, the object region is examined whether it is human or not. For this recognition, the region-based shape descriptor, angular radial transform (ART) in MPEG-7, is used to learn and train the shapes of human bodies. When it is decided that the object is human or something to be investigated, the face region is detected. Finally, the face or object region is tracked in the video, and the pan/tilt/zoom (PTZ) controllable camera tracks the moving object with the motion information of the object. This paper performs the simulation with the real CCTV cameras and their communication protocol. According to the experiments, the proposed system is able to track the moving object(human) automatically not only in the image domain but also in the real 3-D space. The proposed system reduces the human supervisors and improves the surveillance efficiency with the computer vision techniques.

• 방송공학회논문지
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• 제27권4호
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• pp.519-526
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• 2022

동영상 콘텐츠 편집 시 등장인물을 구분하고 식별하는 작업은 많은 시간과 노력이 요구되는 작업이다. 노동 집약적 특성이 있는 미디어 편집 작업 시 인공지능 기술을 활용하면 미디어 제작 시간을 획기적으로 줄일 수 있어 창작과정의 효율성 향상에 도움을 줄 수 있다. 본 논문에서는 동영상 편집을 위한 인물 식별 및 검색 작업을 자동화하기 위해 다수의 인공지능 기술을 혼합하여 활용하는 기법을 제안한다. 객체 검출, 얼굴 검출, 자세 예측 기법을 사용하여 인물 객체에 대한 특징 정보를 수집하고, 수집된 정보를 바탕으로 얼굴 인식, 색 공간 분석 기법 등을 활용하여 인물 객체 식별 정보를 생성한다. 인물 특징 및 식별 정보는 편집 대상 영상의 각 프레임에 대해서 수집되며 영상 편집을 위한 프레임 단위 검색을 위한 메타데이터로 사용된다.

• 반도체디스플레이기술학회지
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• 제17권4호
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• pp.105-108
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• 2018

Face Detection is an essential first step of the face recognition, and this is significant effects on face feature extraction and the effects of face recognition. Face detection has extensive research value and significance. In this paper, we present and analysis the principle, merits and demerits of the classic AdaBoost face detection and ASM algorithm based on point distribution model, which ASM solves the problems of face detection based on AdaBoost. First, the implemented scheme uses AdaBoost algorithm to detect original face from input images or video stream. Then, it uses ASM algorithm converges, which fit face region detected by AdaBoost to detect faces more accurately. Finally, it cuts out the specified size of the facial region on the basis of the positioning coordinates of eyes. The experimental result shows that the method can detect face rapidly and precisely, with a strong robustness.

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송공학회 2004년도 정기총회 및 학술대회
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• pp.237-240
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• 2004

This paper describes a character retrieval system for TV programs and a set of novel algorithms for detecting and recognizing faces for the system. Our character retrieval system consists of two main components: Face Register and Face Recognizer. The Face Register detects faces in video frames and then guides users to register the detected faces of interest into the database. The Face Recognizer displays the appearance interval of each character on the timeline interface and the list of scenes with the names of characters that appear on each scene. These two components also provide a function to modify incorrect results. which is helpful to provide accurate character retrieval services. In the proposed face detection and recognition algorithms. we reduce the computation time without sacrificing the recognition accuracy by using the DCT/LDA method for face feature extraction. We also develop the character retrieval system in the form of plug-in. By plugging in our system to a cataloguing system. the metadata about the characters in a video can be automatically generated. Through this system, we can easily realize sophisticated on-demand video services which provide the search of scenes of a specific TV star.

• 전기학회논문지
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• 제64권6호
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• pp.900-911
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• 2015

In this paper, 3D face recognition model is designed by using Polynomial based RBFNN(Radial Basis Function Neural Network) and PNN(Polynomial Neural Network). Also recognition rate is performed by this model. In existing 2D face recognition model, the degradation of recognition rate may occur in external environments such as face features using a brightness of the video. So 3D face recognition is performed by using 3D scanner for improving disadvantage of 2D face recognition. In the preprocessing part, obtained 3D face images for the variation of each pose are changed as front image by using pose compensation. The depth data of face image shape is extracted by using Multiple point signature. And whole area of face depth information is obtained by using the tip of a nose as a reference point. Parameter optimization is carried out with the aid of both ABC(Artificial Bee Colony) and PSO(Particle Swarm Optimization) for effective training and recognition. Experimental data for face recognition is built up by the face images of students and researchers in IC&CI Lab of Suwon University. By using the images of 3D face extracted in IC&CI Lab. the performance of 3D face recognition is evaluated and compared according to two types of models as well as point signature method based on two kinds of depth data information.

• 디지털산업정보학회논문지
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• 제12권4호
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• pp.1-12
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• 2016

Digital imaging technology has developed into a state-of-the-art IT convergence, composite industry beyond the limits of the multimedia industry, especially in the field of smart object recognition, face - Application developed various techniques have been actively studied in conjunction with the phone. Recently, face recognition technology through the object recognition technology and evolved into intelligent video detection recognition technology, image recognition technology object detection recognition process applies to skills through is applied to the IP camera, the image object recognition technology with face recognition and active research have. In this paper, we first propose the necessary technical elements of the human factor technology trends and look at the human object recognition based spFACS (Smile Progress Facial Action Coding System) for detecting smiles study plan of the image recognition technology recognizes objects. Study scheme 1). ASM algorithm. By suggesting ways to effectively evaluate psychological research skills through the image object 2). By applying the result via the face recognition object to the tooth area it is detected in accordance with the recognized facial expression recognition of a person demonstrated the effect of extracting the feature points.

• 한국통신학회논문지
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• 제30권10C호
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• pp.983-991
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• 2005

드라마와 같은 비디오에서 사람의 얼굴은 일반적으로 자주 등장하며 비디오 내용을 분석하기 위한 유용한 정보를 제공한다. 얼굴검출은 얼굴인식 및 얼굴영상의 DB 관리와 같은 응용분야에 중요한 역할을 한다. 본 논문에서는 비디오 등장인물 검색을 위한 얼굴검출 기법을 제안하였다. 전체 과정은 크게 세단계로 구성되며 첫 번째 장면전환 검출단계, 두 번째 얼굴영역 검출단계, 마지막으로 얼굴의 특징점인 눈과 입 검출단계로 구성되며, 색상에 기반한 얼굴영역 검출단계에서 발생된 얼굴 특징점을 눈과 입의 검출에 적용하였다. 실험결과 다양한 환경에서 성공적으로 얼굴을 검출하며, 기존의 색상기반 얼굴검출 방법에 비해 측면영상에서 $24\%$의 성능향상을 보였다.