Real Time Face Tracking Based on Facial Feature Matching

碩士 === 國立宜蘭大學 === 資訊工程研究所碩士班 === 99 === In this paper, we propose a real-time system to extract and track people’s facial features effectively. It can also resist rotation, scaling, and parallax of the image. When camera captures video frame, the proposed system can recognize where the face is, and...

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Main Authors: Chou, Chioushan, 周久善
Other Authors: Chen, Weiming
Format: Others
Language:zh-TW
Published: 2011
Online Access:http://ndltd.ncl.edu.tw/handle/23852083394557756885
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spelling ndltd-TW-099NIU073920042016-04-13T04:17:34Z http://ndltd.ncl.edu.tw/handle/23852083394557756885 Real Time Face Tracking Based on Facial Feature Matching 以五官特徵比對為基礎的即時人臉追蹤方法 Chou, Chioushan 周久善 碩士 國立宜蘭大學 資訊工程研究所碩士班 99 In this paper, we propose a real-time system to extract and track people’s facial features effectively. It can also resist rotation, scaling, and parallax of the image. When camera captures video frame, the proposed system can recognize where the face is, and then uses our Dynamic Radial Kernel to record and match facial features in each frame. After getting all the facial features from those frames, we can realize what the user’s movement is happening, such as face direction changing, face rotation, and depth changing, because every frame is in the same time sequence. At last, we map the 2D coordinate to 3D space by perspective transform. The experimental result shows that the proposed method is successful. It can recognize human facial features in several environments robustly. In addition, we implement a human interface system using the proposed method to display an augmented reality (AR) application. In the future work, we will try to improve our algorithm of feature recording, matching, and make it suitable to any content of image. Chen, Weiming 陳偉銘 2011 學位論文 ; thesis 48 zh-TW
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language zh-TW
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description 碩士 === 國立宜蘭大學 === 資訊工程研究所碩士班 === 99 === In this paper, we propose a real-time system to extract and track people’s facial features effectively. It can also resist rotation, scaling, and parallax of the image. When camera captures video frame, the proposed system can recognize where the face is, and then uses our Dynamic Radial Kernel to record and match facial features in each frame. After getting all the facial features from those frames, we can realize what the user’s movement is happening, such as face direction changing, face rotation, and depth changing, because every frame is in the same time sequence. At last, we map the 2D coordinate to 3D space by perspective transform. The experimental result shows that the proposed method is successful. It can recognize human facial features in several environments robustly. In addition, we implement a human interface system using the proposed method to display an augmented reality (AR) application. In the future work, we will try to improve our algorithm of feature recording, matching, and make it suitable to any content of image.
author2 Chen, Weiming
author_facet Chen, Weiming
Chou, Chioushan
周久善
author Chou, Chioushan
周久善
spellingShingle Chou, Chioushan
周久善
Real Time Face Tracking Based on Facial Feature Matching
author_sort Chou, Chioushan
title Real Time Face Tracking Based on Facial Feature Matching
title_short Real Time Face Tracking Based on Facial Feature Matching
title_full Real Time Face Tracking Based on Facial Feature Matching
title_fullStr Real Time Face Tracking Based on Facial Feature Matching
title_full_unstemmed Real Time Face Tracking Based on Facial Feature Matching
title_sort real time face tracking based on facial feature matching
publishDate 2011
url http://ndltd.ncl.edu.tw/handle/23852083394557756885
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