• 제목/요약/키워드: Overcome recognition

검색결과 417건 처리시간 0.029초

Hybrid feature extraction of multimodal images for face recognition

  • Cheema, Usman;Moon, Seungbin
    • 한국정보처리학회:학술대회논문집
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    • 한국정보처리학회 2018년도 추계학술발표대회
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    • pp.880-881
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    • 2018
  • Recently technological advancements have allowed visible, infrared and thermal imaging systems to be readily available for security and access control. Increasing applications of facial recognition for security and access control leads to emerging spoofing methodologies. To overcome these challenges of occlusion, replay attack and disguise, researches have proposed using multiple imaging modalities. Using infrared and thermal modalities alongside visible imaging helps to overcome the shortcomings of visible imaging. In this paper we review and propose hybrid feature extraction methods to combine data from multiple imaging systems simultaneously.

Feature Extraction Method for the Character Recognition of the Low Resolution Document

  • Kim, Dae-Hak;Cheong, Hyoung-Chul
    • Journal of the Korean Data and Information Science Society
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    • 제14권3호
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    • pp.525-533
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    • 2003
  • In this paper we introduce some existing preprocessing algorithm for character recognition and consider feature extraction method for the recognition of low resolution document. Image recognition of low resolution document including fax images can be frequently misclassified due to the blurring effect, slope effect, noise and so on. In order to overcome these difficulties in the character recognition we considered a mesh feature extraction and contour direction code feature. System for automatic character recognition were suggested.

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Motion Recognition using Principal Component Analysis

  • Kwon, Yong-Man;Kim, Jong-Min
    • Journal of the Korean Data and Information Science Society
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    • 제15권4호
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    • pp.817-823
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    • 2004
  • This paper describes a three dimensional motion recognition algorithm and a system which adopts the algorithm for non-contact human-computer interaction. From sequence of stereos images, five feature regions are extracted with simple color segmentation algorithm and then those are used for three dimensional locus calculation precess. However, the result is not so stable, noisy, that we introduce principal component analysis method to get more robust motion recognition results. This method can overcome the weakness of conventional algorithms since it directly uses three dimensional information motion recognition.

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포즈 인식에서 효율적 특징 추출을 위한 3차원 데이터의 차원 축소 (3D Data Dimension Reduction for Efficient Feature Extraction in Posture Recognition)

  • 경동욱;이윤리;정기철
    • 정보처리학회논문지B
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    • 제15B권5호
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    • pp.435-448
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    • 2008
  • 사용자 포즈의 3차원 데이터 생성을 통한 3차원 포즈 인식은 2차원 포즈 인식의 문제점을 해결하기 위해서 많이 연구되고 있지만, 3차원 표면 데이터의 방대한 양으로 포즈 인식에서 중요한 특징 추출(feature extraction)이 어렵고 수행 시간이 많이 걸리는 문제점을 가지고 있다. 본 논문에서는 3차원 포즈 인식의 두 가지 문제점인 특징 추출의 어려움과 느린 처리속도를 개선하기 위해서 3차원 형상복원 기술로 모델의 3차원 표면 점들로 구성된 데이터를 2차원 데이터로 변환하는 차원 축소(dimension reduction) 방법을 제안한다. 실린더형 외곽점을 이용한 메쉬없는 매개변수화(meshless parameterization) 방법은 방대한 데이터인 3차원 포즈 데이터를 2차원 데이터로 변환하여 특징 추출과 매칭과정의 연산 속도를 향상 시키며, 특징 추출의 효율성 검증을 위해 간단한 환경에서 실험이 가능한 손 포즈 인식 및 인간 포즈 인식에 적용하였다.

ART와 다층 퍼셉트론을 이용한 얼굴인식 시스템의 성능분석 (Performance Analysis of Face Image Recognition System Using A R T Model and Multi-layer perceptron)

  • 김영일;안민옥
    • 전자공학회논문지B
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    • 제30B권2호
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    • pp.69-77
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    • 1993
  • Automatic image recognition system is essential for a better man-to machine interaction. Because of the noise and deformation due to the sensor operation, it is not simple to build an image recognition system even for the fixed images. In this paper neural network which has been reported to be adequate for pattern recognition task is applied to the fixed and variational(rotation, size, position variation for the fixed image)recognition with a hope that the problems of conventional pattern recognition techniques are overcome. At fixed image recognition system. ART model is trained with face images obtained by camera. When recognizing an matching score. In the test when wigilance level 0.6 - 0.8 the system has achievel 100% correct face recognition rate. In the variational image recognition system, 65 invariant moment features sets are taken from thirteen persons. 39 data are taken to train multi-layer perceptron and other 26 data used for testing. The result shows 92.5% recognition rate.

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휴먼 케어를 위한 초실감 감성 상호작용 기술 (Affective Interaction Technologies for Human Care)

  • 김진서;박창준;이기석;김명규;유원영;지형근;정일권
    • 전자통신동향분석
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    • 제36권1호
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    • pp.43-53
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    • 2021
  • Super-realistic content technology has recently attracted attention as a core of the "new normal" that can overcome the spatial constraints caused by pandemics. It is moreover the core that allows users in remote locations to meet and engage in various social, cultural, and economic activities based on a network. Content technology is rapidly spreading beyond the existing entertainment area to various industries as an innovative tool that can be used to overcome space-time constraints and improve the productivity of industrial sites, because reality and virtual reality are now super-connected with ultra-low latency. However, existing services such as teleconferencing and tele-collaboration do not provide a level of realism that replaces face-to-face services, and various technical requirements have been proposed to overcome this. The trends in core technologies such as XR twins, hyper-realistic reproduction, sensory interaction, and emotional recognition technology, which are necessary for interactive realistic content that leads to feelings, from reproduction to experience and emotion, are explained. In this article, our aim is to present the future of realistic content that enables human care and can even overcome psychological difficulties such as the "Corona blues".

Noise-Robust Speaker Recognition Using Subband Likelihoods and Reliable-Feature Selection

  • Kim, Sung-Tak;Ji, Mi-Kyong;Kim, Hoi-Rin
    • ETRI Journal
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    • 제30권1호
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    • pp.89-100
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    • 2008
  • We consider the feature recombination technique in a multiband approach to speaker identification and verification. To overcome the ineffectiveness of conventional feature recombination in broadband noisy environments, we propose a new subband feature recombination which uses subband likelihoods and a subband reliable-feature selection technique with an adaptive noise model. In the decision step of speaker recognition, a few very low unreliable feature likelihood scores can cause a speaker recognition system to make an incorrect decision. To overcome this problem, reliable-feature selection adjusts the likelihood scores of an unreliable feature by comparison with those of an adaptive noise model, which is estimated by the maximum a posteriori adaptation technique using noise features directly obtained from noisy test speech. To evaluate the effectiveness of the proposed methods in noisy environments, we use the TIMIT database and the NTIMIT database, which is the corresponding telephone version of TIMIT database. The proposed subband feature recombination with subband reliable-feature selection achieves better performance than the conventional feature recombination system with reliable-feature selection.

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잡음 환경에서 음성 인식률 향상에 필요한 MEMS 장치 개발에 관한 연구 (The research on the MEMS device improvement which is necessary for the noise environment in the speech recognition rate improvement)

  • 양기웅;이형근
    • 한국정보통신학회논문지
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    • 제22권12호
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    • pp.1659-1666
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    • 2018
  • 입력된 소리가 음성과 음향이 혼재된 경우 잡음의 영향으로 음성 인식률이 저하됨을 알 수 있으며 S/W적 처리 한계를 극복코자 H/W 장치인 MEMS 장치를 개발하여 음성 인식률을 향상시켰다. MEMS 마이크로폰 장치는 음성을 입력하는 장치로서 다양한 모양으로 구현되어 사용된다. 기존 MEMS 마이크로폰은 일반적으로 우수한 성능을 발휘하나 잡음 과 같은 특수 환경에선 음성과 음향이 혼재되어 처리 성능이 저하되는 문제점이 발생됨을 알 수 있었다. 이러한 문제점을 개선코자 초기 입력장치에 음성 특성을 구분하여 검출할 수 있는 신규 고안된 MEMS 장치를 사용하여 향상시켰다.

An Efficient Binarization Method for Vehicle License Plate Character Recognition

  • Yang, Xue-Ya;Kim, Kyung-Lok;Hwang, Byung-Kon
    • 한국멀티미디어학회논문지
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    • 제11권12호
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    • pp.1649-1657
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    • 2008
  • In this paper, to overcome the failure of binarization for the characters suffered from low contrast and non-uniform illumination in license plate character recognition system, we improved the binarization method by combining local thresholding with global thresholding and edge detection. Firstly, apply the local thresholding method to locate the characters in the license plate image and then get the threshold value for the character based on edge detector. This method solves the problem of local low contrast and non-uniform illumination. Finally, back-propagation Neural Network is selected as a powerful tool to perform the recognition process. The results of the experiments i1lustrate that the proposed binarization method works well and the selected classifier saves the processing time. Besides, the character recognition system performed better recognition accuracy 95.7%, and the recognition speed is controlled within 0.3 seconds.

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손 제스처 인식을 통한 인체 아바타의 지능적 자율 이동에 관한 연구 (Study on Intelligent Autonomous Navigation of Avatar using Hand Gesture Recognition)

  • 김종성;박광현;김정배;도준형;송경준;민병의;변증남
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 1999년도 추계종합학술대회 논문집
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    • pp.483-486
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    • 1999
  • In this paper, we present a real-time hand gesture recognition system that controls motion of a human avatar based on the pre-defined dynamic hand gesture commands in a virtual environment. Each motion of a human avatar consists of some elementary motions which are produced by solving inverse kinematics to target posture and interpolating joint angles for human-like motions. To overcome processing time of the recognition system for teaming, we use a Fuzzy Min-Max Neural Network (FMMNN) for classification of hand postures

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