• The Journal of the Korea Contents Association
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• v.6 no.12
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• pp.1-11
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• 2006

Many research demonstrations and commercial applications have been tried to develop face detection and recognition systems. Human face detection plays an important role in applications such as access control and video surveillance, human computer interface, identity authentication, etc. There are some special problems such as a face connected with background, faces connected via the skin color, and a face divided into several small parts after skin region segmentation in generally. It can be allowed many face detection techniques to solve the first and second problems. However, it is not easy to detect a face divided into several parts of regions for reason of different illumination conditions in the third problem. Therefore, we propose an efficient modified skin segmentation algorithm to solve this problem because the typical region segmentation algorithm can not be used to. Our algorithm detects skin regions over the entire image, and then generates face candidate regions using our skin segmentation algorithm For each face candidate, we implement the procedure of region merging for divided regions in order to make a region using adjacency between homogeneous regions. We utilize various different searching window sizes to detect different size faces and a face detection classifier based on a back-propagation algorithm in order to verify whether the searching window contains a face or not.

• 한국HCI학회:학술대회논문집
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• 2008.02b
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• pp.60-63
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• 2008

The sony Eytoy is developed on Playstation 2 using webcam for detecting human. A user see his appearance in television and become real gamer in the game. It is very different interface compared with ordinary video game which uses joystick. Although Eyetoy already was made for commercial products but the interface method still is interesting and can be added with many techniques like gesture recognition. In this paper, we have developed game interface with image processing for human hand and face detection and with game graphic module. And we realize one example game for busting balloons and demonstrated the game interface abilities. We will open this project for other developers and will be developed very much.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2003.10a
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• pp.236-238
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• 2003

Human face detection is often the first step in applications such as video surveillance, human computer interface, fare recognition, and image database management. We have constructed a simple and fast system to detect frontal human faces in complex environment and different illumination. This paper presents a fast segmentation method to combine neighboring pixels with similar hue. The algorithm constructs eye, mouth, and boundary maps for verifying each fare candidate. We test the system on images in complex environment and with confusing objects. The experiment shows a robust detection result with few false detected fates.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.3B
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• pp.529-540
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• 2000

This is paper presents the semantic based rate-control method which is based on very low bit rate video coding standards H.263 plus, applied on very low bit rate applications. Previous rate control methods control the generated bit rates by setting the optimum quantization parameters per macro block unit on frame. But, in this paper, we added the pre-processing algorithm, semantic region recognition and assignment of priority algorithm, to obtain the subjective quality enhancement. This work aims to improve the subjective quality of skin color region or face by using unimportant background region's bit resources.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.9
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• pp.1183-1189
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• 2021

There have been recently an increasing number of people working out at home. However, many of them do not have face-to-face guidance from experts, so they cannot effectively correct their wrong pose. This may lead to strain and injury to those doing home training. To tackle this problem, this paper proposes a video data-based pose classification and correction system for home training. The proposed system classifies poses using the multi-layer perceptron and pose estimation model, and corrects poses based on joint angels estimated. A voting algorithm that considers the results of successive frames is applied to improve the performance of the pose classification model. Multi-layer perceptron model for post classification shows the highest accuracy with 0.9. In addition, it is shown that the proposed voting algorithm improves the accuracy to 0.93.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.4 no.4
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• pp.618-632
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• 2010

This paper presents a novel approach to control the augmented reality (AR) objects robustly in a marker-less AR system by fingertip tracking and hand pattern recognition. It is known that one of the promising ways to develop a marker-less AR system is using human's body such as hand or face for replacing traditional fiducial markers. This paper introduces a real-time method to manipulate the overlaid virtual objects dynamically in a marker-less AR system using both hands with a single camera. The left bare hand is considered as a virtual marker in the marker-less AR system and the right hand is used as a hand mouse. To build the marker-less system, we utilize a skin-color model for hand shape detection and curvature-based fingertip detection from an input video image. Using the detected fingertips the camera pose are estimated to overlay virtual objects on the hand coordinate system. In order to manipulate the virtual objects rendered on the marker-less AR system dynamically, a vision-based hand control interface, which exploits the fingertip tracking for the movement of the objects and pattern matching for the hand command initiation, is developed. From the experiments, we can prove that the proposed and developed system can control the objects dynamically in a convenient fashion.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.10a
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• pp.127-130
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• 2007

Skin detection research is important role in the 3G of mobile phone for video telephony and security system by using face recognition. We propose skin detection algorithm as preprocessing to the face recognition, and use YCbCr color space. In existing skin detection algorithm using CbCr, skin colors that is brightened by camera flash or sunlight at outdoor in images doesn't acknowledged the skin region. In order to detect skin region accuracy into any circumstance, this paper proposes 3-channel skin detection algorithm.

• Proceedings of the Korean Information Science Society Conference
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• 1998.10c
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• pp.452-454
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• 1998

본 논문에서는 MPEG 압축 비디오 상에서 얼굴 영역을 추출하고 이를 인식하는 방법에 대하여 제안한다. 제안된 방법은 크게 MPEG 압축 비디오의 처리를 위한 축소된 DC 영상의 구성 단계, 축소된 DC 영상에서의 얼굴 영역 추출 단계, 그리고 얼굴 영역이 추출된 프레임에 대한 압축 복원 및 얼굴 인식의 3단계로 구성되어있다. DC 영상의 구성 단계에서는 압축 복원 없이 DCT 계수의 DC 값과 2개의 AC 값만을 사용하여 부분적인 2차원 역 DCT 변환을 이용한 방법을 사용하였으며, 얼굴 영역 추출 단계에서는 DC 영상에 대해 얼굴의 색상 및 형태 정보를 이용한 얼굴 후보 영역 추출 방법과 K-L 변환 및 역 변환의 오차에 의한 얼굴 영역 추출 방법을 사용하였다. 얼굴 인식 단계에서는 얼굴 영역이 추출된 프레임에 대하여 GOP 단위의 압축 복원을 수행한 후 고유 얼굴 영상을 이용한 방법으로 얼굴 인식을 수행하였다. 제안된 방법의 성능을 검증하기 위하여 뉴스와 드라마 MPEG 비디오를 대상으로 실험을 수행하였으며, 실험 결과 제안된 방법이 효율적임을 알 수 있었다.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.683-684
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• 2006

본 논문은 비디오기반의 얼굴인식에 있어서 환경의 변화나 왜곡, 노이즈 등으로 발생할 수 있는 부분적인 가림현상(Partial Occlusion)에 대한 처리기법을 제시한다. 인증되는 각 사람은 하나의 Manifold 를 구성하며 각 Manifold 는 m 개의 pose-Manifold 로 구성된다. Pose-Manifold 를 구성하기 위한 학습데이터는 매우 유사한 포즈들로 구성되기 때문에 얼굴을 이루는 영역의 픽셀에 대한 Intensity 의 변화는 크지 않다. 입력되는 이미지의 Intensity 를 학습데이터의 Intensity 의 변화량을 고려한 Intensity Distortion 을 이용하면 Occlusion 이 발생한 영역을 찾을 수 있고, Occlusion 이 발생한 정도에 따라 가중치를 부여할 수 있다. 이렇게 Occlusion 에 따라 영역에 중요도를 다르게 하여 얼굴인식률을 높이고자 한다. 실험에서는 제시하는 Mask 를 사용하지 않았을 경우와 기존에 제시된 알고리즘과의 성능을 비교한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2010.11a
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• pp.565-567
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• 2010

일반적으로 얼굴 인식 방법에는 템플릿 기반 통계적 기법들이 사용되고 있다. 이 방법들은 2차원 영상을 고차원 벡터로 표현하여 특징을 추출한다. 그러나 많은 이미지와 비디오 데이터는 본래 텐서로 표현된다. 따라서, 본 논문에서는 벡터 표현보다는 직접적인 텐서 표현으로 특징들을 추출하기 위해 텐서 얼굴의 다선형 주성분 분석(MPCA: Multilinear Principal Component Analysis) 기법을 이용한 동영상 기반 얼굴인식에 대해 다룬다. 마지막으로, u-로봇 테스트베드 환경에서 구축된 얼굴 인식 데이터 베이스를 이용하여 제안된 방법과 기존 방법들의 인식처리시간과 성능을 비교한다.