• Title/Summary/Keyword: Face Factor Detection

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Using a Multi-Faced Technique SPFACS Video Object Design Analysis of The AAM Algorithm Applies Smile Detection (다면기법 SPFACS 영상객체를 이용한 AAM 알고리즘 적용 미소검출 설계 분석)

  • Choi, Byungkwan
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.11 no.3
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    • pp.99-112
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    • 2015
  • Digital imaging technology has advanced beyond the limits of the multimedia industry IT convergence, and to develop a complex industry, particularly in the field of object recognition, face smart-phones associated with various Application technology are being actively researched. Recently, face recognition technology is evolving into an intelligent object recognition through image recognition technology, detection technology, the detection object recognition through image recognition processing techniques applied technology is applied to the IP camera through the 3D image object recognition technology Face Recognition been actively studied. In this paper, we first look at the essential human factor, technical factors and trends about the technology of the human object recognition based SPFACS(Smile Progress Facial Action Coding System)study measures the smile detection technology recognizes multi-faceted object recognition. Study Method: 1)Human cognitive skills necessary to analyze the 3D object imaging system was designed. 2)3D object recognition, face detection parameter identification and optimal measurement method using the AAM algorithm inside the proposals and 3)Face recognition objects (Face recognition Technology) to apply the result to the recognition of the person's teeth area detecting expression recognition demonstrated by the effect of extracting the feature points.

Automatic Speechreading Feature Detection Using Color Information (색상 정보를 이용한 자동 독화 특징 추출)

  • Lee, Kyong-Ho;Yang, Ryong;Rhee, Sang-Burm
    • Journal of the Korea Society of Computer and Information
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    • v.13 no.6
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    • pp.107-115
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    • 2008
  • Face feature detection plays an important role in application such as automatic speechreading, human computer interface, face recognition, and face image database management. We proposed a automatic speechreading feature detection algorithm for color image using color information. Face feature pixels is represented for various value because of the luminance and chrominance in various color space. Face features are detected by amplifying, reducing the value and make a comparison between the represented image. The eye and nose position, inner boundary of lips and the outer line of the tooth is detected and show very encouraging result.

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Face Tracking Using Face Feature and Color Information (색상과 얼굴 특징 정보를 이용한 얼굴 추적)

  • Lee, Kyong-Ho
    • Journal of the Korea Society of Computer and Information
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    • v.18 no.11
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    • pp.167-174
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    • 2013
  • TIn this paper, we find the face in color images and the ability to track the face was implemented. Face tracking is the work to find face regions in the image using the functions of the computer system and this function is a necessary for the robot. But such as extracting skin color in the image face tracking can not be performed. Because face in image varies according to the condition such as light conditions, facial expressions condition. In this paper, we use the skin color pixel extraction function added lighting compensation function and the entire processing system was implemented, include performing finding the features of eyes, nose, mouth are confirmed as face. Lighting compensation function is a adjusted sine function and although the result is not suitable for human vision, the function showed about 4% improvement. Face features are detected by amplifying, reducing the value and make a comparison between the represented image. The eye and nose position, lips are detected. Face tracking efficiency was good.

ASM Algorithm Applid to Image Object spFACS Study on Face Recognition (영상객체 spFACS ASM 알고리즘을 적용한 얼굴인식에 관한 연구)

  • Choi, Byungkwan
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.12 no.4
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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.

Driver Drowsiness Detection Algorithm based on Facial Features (얼굴 특징점 기반의 졸음운전 감지 알고리즘)

  • Oh, Meeyeon;Jeong, Yoosoo;Park, Kil-Houm
    • Journal of Korea Multimedia Society
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    • v.19 no.11
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    • pp.1852-1861
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    • 2016
  • Drowsy driving is a significant factor in traffic accidents, so driver drowsiness detection system based on computer vision for convenience and safety has been actively studied. However, it is difficult to accurately detect the driver drowsiness in complex background and environmental change. In this paper, it proposed the driver drowsiness detection algorithm to determine whether the driver is drowsy through the measurement standard of a yawn, eyes drowsy status, and nod based on facial features. The proposed algorithm detect the driver drowsiness in the complex background, and it is robust to changes in the environment. The algorithm can be applied in real time because of the processing speed faster. Throughout the experiment, we confirmed that the algorithm reliably detected driver drowsiness. The processing speed of the proposed algorithm is about 0.084ms. Also, the proposed algorithm can achieve an average detection rate of 98.48% and 97.37% for a yawn, drowsy eyes, and nod in the daytime and nighttime.

An Improved Face Detection Method Using a Hybrid of Hausdorff and LBP Distance (Hausdorff와 LBP 거리의 융합을 이용한 개선된 얼굴검출)

  • Park, Seong-Chun;Koo, Ja-Young
    • Journal of the Korea Society of Computer and Information
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    • v.15 no.11
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    • pp.67-73
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    • 2010
  • In this paper, a new face detection method that is more accurate than the conventional methods is proposed. This method utilizes a hybrid of Hausdorff distance based on the geometric similarity between the two sets of points and the LBP distance based on the distribution of local micro texture of an image. The parameters for normalization and the optimal blending factor of the two different metrics were calculated from training sample images. Popularly used face database was used to show that the proposed method is more effective and robust to the variation of the pose, illumination, and back ground than the methods based on the Hausdorff distance or LBP distance. In the particular case, the average error distance between the detected and the true face location was reduced to 47.9% of the result of LBP method, and 22.8% of the result of Hausdorff method.

Research on depression and emergency detection model using smartphone sensors (스마트폰 센서를 통한 우울증 탐지 및 위급상황 탐지 모델 연구)

  • Mingeun Son;Gangpyo Lee;Jae Yong Park;Min Choi
    • Smart Media Journal
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    • v.12 no.3
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    • pp.9-18
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    • 2023
  • Due to the deepening of COVID-19, high-intensity social distancing has been prolonged and many social problems have been cured. In particular, physical and psychological isolation occurred due to the non-face-to-face system and a lot of damage occurred. The various social problems caused by Corona acted as severe stress for all those affected by Corona 19, and eventually acted as a factor threatening mental health such as depression. While the number of people suffering from mental illness is increasing, the actual use of mental health services is low. Therefore, it is necessary to establish a system for people suffering from mental health problems. Therefore, in this study, depression detection and emergency detection models were constructed based on sensor information using smartphones from depressed subjects and general subjects. For the detection of depression and emergencies, VAE, DAGMM, ECOD, COPOD, and LGBM algorithms were used. As a result of the study, the depression detection model had an F1 score of 0.93 and the emergency situation detection model had an F1 score of 0.99. direction.

A Study on the Development of Automatic Detection and Warning system while Drowsy Driving (졸음운전의 자동 검출 및 각성 시스템 개발에 관한 연구)

  • Kim, Nam-Gyun;Jeong, Gyeong-Ho;Kim, Beop-Jung
    • Journal of Biomedical Engineering Research
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    • v.18 no.3
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    • pp.315-323
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    • 1997
  • Driving is a complex vigilance task that includes improper lookout, excessive speed and inattention. The primary objective of this research is to detect driver drowsiness so that the driver can be alerted to an impending traffic accident in performance. We developed the automatic detection and warning system during drowsy driving. A drowsiness detection system must be able to monitor driver status and detect the detrimental changes of a driver performance. Eyeblink has been found to be a reliable factor of drowsiness detection in earlier studies. As an additional parameter, we also considered the yawning which often occurs in a low vigilance state and predicts the drowsy state. We used a computer vision method to extract the eyeblink and yawning in the face image sequences. When the drowsy state was detected, the driver was refreshed by alarming device and menthol scent generator after deciding the warning level by fuzzy logic. For the evaluation of our system, we measured the physiological parameters such as EOG and EEG. The results indicated that it is possible to detect and alert the driver drowsiness temporarily or continuously by using our system.

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Influence of Weak Ground Ahead of the Tunnel Face on 3D-displacement and Face Extrusion (막장전방의 연약층이 터널 3차원변위 및 막장 수평변위에 미치는 영향)

  • Jeon, Je-Sung
    • Journal of the Korean Geotechnical Society
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    • v.19 no.6
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    • pp.189-206
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    • 2003
  • During tunnel excavation in urban area a systematic monitoring is important for the purpose of determination of support type and quantity, as well as for the control of stability of both surface structures and the tunnel itself due to the frequently, and in many cases, abruptly changing ground condition. In Austria absolute displacement monitoring methods have replaced relative displacement measurements by geodetic methods to a large extent. Prompt detection of weak ground ahead of the tunnel face as well as better adjustment of excavation and support to the geotechnical conditions is possible with the help of the improved methods of data evaluation on sites. Deformation response of the ground to excavation starts ahead of the tunnel face, therefore, the deformation and state of the tunnel advance core is the key factor of the whole deformation process after excavation. In other words, the rigidity and state of the advance core play a determining role in the stability of both surface structures and the tunnel itself. This paper presents the results from detailed three-dimensional numerical studies, exploring vertical displacements, vector orientations and extrusions on tunnel face during the progressive advancement for the shallow tunnel in various geotechnical conditions.

2 Factor Authentication Using Face Recognition and One-Time Password for Spoofing Attack Prevention (안면 인식 스푸핑 방지를 위한 얼굴인식과 OTP를 이용한 2 Factor 인증)

  • Yun, Jung Bin;Jung, Ji Eun;Jo, Hyo Ju;Han, Seung Min;Kim, Sun Hee
    • Proceedings of the Korea Information Processing Society Conference
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    • 2020.11a
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    • pp.640-643
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    • 2020
  • 사진, 동영상 또는 3D 프린터로 변조된 얼굴을 이용한 안면인식 보안 우회 사례가 증가하였다. 따라서 본 논문에서는 얼굴인증 단계인 본인 여부와 Liveness Detection 및 OTP를 통한 다중인증 프레임워크를 구현함으로써 기존 단일인증 대비 더욱 안전한 인증 환경을 기대한다.