• Title/Summary/Keyword: 포즈 각도 예측

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Face Recognition Robust to Pose Variations (포즈 변화에 강인한 얼굴 인식)

  • 노진우;문인혁;고한석
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.41 no.5
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    • pp.63-69
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    • 2004
  • This paper proposes a novel method for achieving pose-invariant face recognition using cylindrical model. On the assumption that a face is shaped like that of a cylinder, we estimate the object's pose and then extract the frontal face image via a pose transform with previously estimated pose angle. By employing the proposed pose transform technique we can increase the face recognition performance using the frontal face images. Through representative experiments, we achieved an increased recognition rate from 61.43% to 94.76% by the pose transform. Additionally, the recognition rate with the proposed method achieves as good as that of the more complicated 3D face model.

Stereo-based Robust Human Detection on Pose Variation Using Multiple Oriented 2D Elliptical Filters (방향성 2차원 타원형 필터를 이용한 스테레오 기반 포즈에 강인한 사람 검출)

  • Cho, Sang-Ho;Kim, Tae-Wan;Kim, Dae-Jin
    • Journal of KIISE:Software and Applications
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    • v.35 no.10
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    • pp.600-607
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    • 2008
  • This paper proposes a robust human detection method irrespective of their pose variation using the multiple oriented 2D elliptical filters (MO2DEFs). The MO2DEFs can detect the humans regardless of their poses unlike existing object oriented scale adaptive filter (OOSAF). To overcome OOSAF's limitation, we introduce the MO2DEFs whose shapes look like the oriented ellipses. We perform human detection by applying four different 2D elliptical filters with specific orientations to the 2D spatial-depth histogram and then by taking the thresholds over the filtered histograms. In addition, we determine the human pose by using convolution results which are computed by using the MO2DEFs. We verify the human candidates by either detecting the face or matching head-shoulder shapes over the estimated rotation. The experimental results showed that the accuracy of pose angle estimation was about 88%, the human detection using the MO2DEFs outperformed that of using the OOSAF by $15{\sim}20%$ especially in case of the posed human.

Error Quantification of Photogrammetric 6DOF Pose Estimation (사진계측기반 6자유도 포즈 예측의 오차 정량화)

  • Kim, Sang-Jin;You, Heung-Cheol;Reu, Taekyu
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.41 no.5
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    • pp.350-356
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    • 2013
  • Photogrammetry has been widely used for measuring the important physical quantities in aerospace areas because it is a remote and non-contact measurement method. In this study, we analyzed photogrammetric error which can be occur in six degrees of freedom(6DOF) analysis among coordinates systems with single camera. Error analysis program were developed, and validated using geometric problem converted from imaging process. We analogized that the statistic from estimated camera pose which is need to 6DOF analysis is normally distributed, and quantified the photogrammetric error using estimated population standard deviation.

A Real-time Hand Pose Recognition Method with Hidden Finger Prediction (은닉된 손가락 예측이 가능한 실시간 손 포즈 인식 방법)

  • Na, Min-Young;Choi, Jae-In;Kim, Tae-Young
    • Journal of Korea Game Society
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    • v.12 no.5
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    • pp.79-88
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    • 2012
  • In this paper, we present a real-time hand pose recognition method to provide an intuitive user interface through hand poses or movements without a keyboard and a mouse. For this, the areas of right and left hands are segmented from the depth camera image, and noise removal is performed. Then, the rotation angle and the centroid point of each hand area are calculated. Subsequently, a circle is expanded at regular intervals from a centroid point of the hand to detect joint points and end points of the finger by obtaining the midway points of the hand boundary crossing. Lastly, the matching between the hand information calculated previously and the hand model of previous frame is performed, and the hand model is recognized to update the hand model for the next frame. This method enables users to predict the hidden fingers through the hand model information of the previous frame using temporal coherence in consecutive frames. As a result of the experiment on various hand poses with the hidden fingers using both hands, the accuracy showed over 95% and the performance indicated over 32 fps. The proposed method can be used as a contactless input interface in presentation, advertisement, education, and game applications.

Rectified Stereoscopic Image Generation Using Two-Step Pose Estimation (2 단계 포즈 예측 기반 교정된 입체 영상 생성)

  • Moon, Hyun-Jung;Jeong, Da-Un;Kim, Man-Bae
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2010.07a
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    • pp.250-251
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    • 2010
  • 디지털 카메라의 보급으로 이미지처리 분야에서 정지영상을 이용한 다양한 기술 개발이 화두가 되고 있다. 스테레오 영상은 정지영상보다 소비자의 시각적 욕구를 충족시킬 수 있는 영상을 표현하기 때문에 스테레오 영상기술에 대한 관심이 높아지고 있다. 본 논문에서는 하나의 카메라로 같은 객체를 다른 위치에서 찍은 2장의 정지영상을 통해 스테레오 영상을 제작하는 방법을 제안한다. 실험 영상으로 디지털카메라로 찍은 좌측 영상과 우측영상을 사용한다. 두 영상의 제어점이 될 코너를 검출한 후, 유클리드의 좌표로 바꿔준다. 이 좌표들을 통해 각 제어점에 인접해 있는 좌표 4개를 추출한다. 이 인접 좌표들이 우측 정지 영상의 인접 좌표에 매칭 되는 횟수를 계산하여, 가장 많은 매칭 좌표를 갖는 스케일 요소로 좌측 정지영상을 회전과 이동시켜 목적 영상인 우측 영상에 매칭시킴으로써 스테레오 영상을 구현한다.

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