• Title/Summary/Keyword: facial region detection

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Presentation control of a computer using hand motion identification rules (손동작 식별 규칙을 이용한 컴퓨터의 프레젠테이션 제어)

  • Lee, Kyu-Won
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.22 no.9
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    • pp.1172-1178
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    • 2018
  • A system that control computer presentations by using the hand motion recognition and identification is proposed. The system recognizes and identifies various types of motion in hand motion, controlls the presentation without additional control devices. To recognize hand movements, it performs a face and hand region detection. Facial area is detected using Haar classifier and hand region is extracted according to skin color information on HSV color model. The face area is used to determine the beginning and end of hand gestures, the size and direction of motion. It recognizes various hand gestures and uses them to control computer presentations according to the hand motion identification rules that are proposed and set horizontal and vertical axes from the face area. It is confirmed that 97.2% recognition rate is obtained in about 1200 hand motion recognition experiments and the proposed algorithm is valid in presentation control.

Wavelet Transform-based Face Detection for Real-time Applications (실시간 응용을 위한 웨이블릿 변환 기반의 얼굴 검출)

  • 송해진;고병철;변혜란
    • Journal of KIISE:Software and Applications
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    • v.30 no.9
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    • pp.829-842
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    • 2003
  • In this Paper, we propose the new face detection and tracking method based on template matching for real-time applications such as, teleconference, telecommunication, front stage of surveillance system using face recognition, and video-phone applications. Since the main purpose of paper is to track a face regardless of various environments, we use template-based face tracking method. To generate robust face templates, we apply wavelet transform to the average face image and extract three types of wavelet template from transformed low-resolution average face. However template matching is generally sensitive to the change of illumination conditions, we apply Min-max normalization with histogram equalization according to the variation of intensity. Tracking method is also applied to reduce the computation time and predict precise face candidate region. Finally, facial components are also detected and from the relative distance of two eyes, we estimate the size of facial ellipse.

Technology Development for Non-Contact Interface of Multi-Region Classifier based on Context-Aware (상황 인식 기반 다중 영역 분류기 비접촉 인터페이스기술 개발)

  • Jin, Songguo;Rhee, Phill-Kyu
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.20 no.6
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    • pp.175-182
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    • 2020
  • The non-contact eye tracking is a nonintrusive human-computer interface providing hands-free communications for people with severe disabilities. Recently. it is expected to do an important role in non-contact systems due to the recent coronavirus COVID-19, etc. This paper proposes a novel approach for an eye mouse using an eye tracking method based on a context-aware based AdaBoost multi-region classifier and ASSL algorithm. The conventional AdaBoost algorithm, however, cannot provide sufficiently reliable performance in face tracking for eye cursor pointing estimation, because it cannot take advantage of the spatial context relations among facial features. Therefore, we propose the eye-region context based AdaBoost multiple classifier for the efficient non-contact gaze tracking and mouse implementation. The proposed method detects, tracks, and aggregates various eye features to evaluate the gaze and adjusts active and semi-supervised learning based on the on-screen cursor. The proposed system has been successfully employed in eye location, and it can also be used to detect and track eye features. This system controls the computer cursor along the user's gaze and it was postprocessing by applying Gaussian modeling to prevent shaking during the real-time tracking using Kalman filter. In this system, target objects were randomly generated and the eye tracking performance was analyzed according to the Fits law in real time. It is expected that the utilization of non-contact interfaces.

A Review on Child Abuse in Pediatric Dentistry (아동학대에 대한 소아치과적 고찰)

  • Jeong, Taesung;Kim, Jiyeon
    • Journal of the korean academy of Pediatric Dentistry
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    • v.43 no.3
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    • pp.334-339
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    • 2016
  • Child abuse often interferes with the normal and healthy development of a child, bringing about various complications and problematic behaviors. Furthermore, such physical, mental abuse or neglect, and sexual abuse on a developing child may have serious effects even until after adolescence. The types of injuries caused by physical abuse vary, but some types of injuries are common. A great number of them can be detected during a routine dental examination because many of these injuries are present in the facial and dental region. Accordingly, in the case of abused children, it is important to find the signs of abuse through regular dental checkups, as many suffer injuries to the face, head and neck area including the oral and perioral area. As a pediatric dentist, it is the legal and social obligation to contribute to preventing and assisting the struggle against child abuse. The authors contemplate ways for all pediatric dental related personnel to find some clinical signs and symptoms of child abuse to help early detection, and to manage the situation properly.

1p36 deletion syndrome confirmed by fluorescence in situ hybridization and array-comparative genomic hybridization analysis

  • Kang, Dong Soo;Shin, Eunsim;Yu, Jeesuk
    • Clinical and Experimental Pediatrics
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    • v.59 no.sup1
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    • pp.14-18
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    • 2016
  • Pediatric epilepsy can be caused by various conditions, including specific syndromes. 1p36 deletion syndrome is reported in 1 in 5,000-10,000 newborns, and its characteristic clinical features include developmental delay, mental retardation, hypotonia, congenital heart defects, seizure, and facial dysmorphism. However, detection of the terminal deletion in chromosome 1p by conventional G-banded karyotyping is difficult. Here we present a case of epilepsy with profound developmental delay and characteristic phenotypes. A 7-year-and 6-month-old boy experienced afebrile generalized seizure at the age of 5 years and 3 months. He had recurrent febrile seizures since 12 months of age and showed severe global developmental delay, remarkable hypotonia, short stature, and dysmorphic features such as microcephaly; small, low-set ears; dark, straight eyebrows; deep-set eyes; flat nasal bridge; midface hypoplasia; and a small, pointed chin. Previous diagnostic work-up, including conventional chromosomal analysis, revealed no definite causes. However, array-comparative genomic hybridization analysis revealed 1p36 deletion syndrome with a 9.15-Mb copy loss of the 1p36.33-1p36.22 region, and fluorescence in situ hybridization analysis (FISH) confirmed this diagnosis. This case highlights the need to consider detailed chromosomal study for patients with delayed development and epilepsy. Furthermore, 1p36 deletion syndrome should be considered for patients presenting seizure and moderate-to-severe developmental delay, particularly if the patient exhibits dysmorphic features, short stature, and hypotonia.

Recognition method using stereo images-based 3D information for improvement of face recognition (얼굴인식의 향상을 위한 스테레오 영상기반의 3차원 정보를 이용한 인식)

  • Park Chang-Han;Paik Joon-Ki
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.43 no.3 s.309
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    • pp.30-38
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    • 2006
  • In this paper, we improved to drops recognition rate according to distance using distance and depth information with 3D from stereo face images. A monocular face image has problem to drops recognition rate by uncertainty information such as distance of an object, size, moving, rotation, and depth. Also, if image information was not acquired such as rotation, illumination, and pose change for recognition, it has a very many fault. So, we wish to solve such problem. Proposed method consists of an eyes detection algorithm, analysis a pose of face, md principal component analysis (PCA). We also convert the YCbCr space from the RGB for detect with fast face in a limited region. We create multi-layered relative intensity map in face candidate region and decide whether it is face from facial geometry. It can acquire the depth information of distance, eyes, and mouth in stereo face images. Proposed method detects face according to scale, moving, and rotation by using distance and depth. We train by using PCA the detected left face and estimated direction difference. Simulation results with face recognition rate of 95.83% (100cm) in the front and 98.3% with the pose change were obtained successfully. Therefore, proposed method can be used to obtain high recognition rate with an appropriate scaling and pose change according to the distance.