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학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
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연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
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Images and Videos that include the human face contain a lot of information. Therefore, accurately extracting human face is a very important issue in the field of computer vision. However, in real life, human faces have various shapes and textures. To adapt to these variations, A model-based approach is one of the best ways in which unknown data can be represented by the model in which it is built. However, the model-based approach has its weaknesses when the motion between two frames is big, it can be either a sudden change of pose or moving with fast speed. In this paper, we propose an enhanced human face-tracking model. This approach included human face detection and motion estimation using Cascaded Convolutional Neural Networks, and continuous human face tracking and modeling correction steps using the Active Appearance Model. A proposed system detects human face in the first input frame and initializes the models. On later frames, Cascaded CNN face detection is used to estimate the target motion such as location or pose before applying the old model and fit new target.
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참고문헌 (12)
참고문헌 신청
/ / http://cvlab.hanyang.ac.kr/tracker_benchmark/datasets.html
C. Bao / 2012 / Real Time Robust L1 Tracker Using Accelerated Proximal Gradient Approach / Conference on Computer Vision and Pattern Recognition : 1830 ~ 1837
C. Zhang / 2014 / Improving multiview face detection with multi-task deep convolutional neural networks / IEEE Winter Conference on Applications of Computer Vision : 1036 ~ 1041
E. N. Arcoverdo Neto / 2014 / Enhanced real-time head pose estimation system for mobile device / Integrated Computer Aided Engineering 21 (3) : 281 ~ 293
H. Li / 2015 / A convolutional neural network cascade for face detection / IEEE Conference on Computer Vision and Pattern Recognition : 5325 ~ 5334
C. Zhang / 2014 / Improving multiview face detection with multi-task deep convolutional neural networks / IEEE Winter Conference on Applications of Computer Vision : 1036 ~ 1041
E. N. Arcoverdo Neto / 2014 / Enhanced real-time head pose estimation system for mobile device / Integrated Computer Aided Engineering 21 (3) : 281 ~ 293
H. Li / 2015 / A convolutional neural network cascade for face detection / IEEE Conference on Computer Vision and Pattern Recognition : 5325 ~ 5334
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