簡易檢索 / 詳目顯示
| 研究生： |
周建豐 jing-Fon Zhuo |
|---|---|
| 論文名稱： |
以多階分割的空間關係做人臉偵測與特徵擷取 |
| 指導教授： |
曾定章
Din-chang Tseng |
| 口試委員: | |
| 學位類別： |
碩士 Master |
| 系所名稱： |
資訊電機學院 - 資訊工程學系 Department of Computer Science & Information Engineering |
| 畢業學年度： | 90 |
| 語文別： | 中文 |
| 論文頁數： | 60 |
| 中文關鍵詞： | 人臉特徵分割 、人臉偵測 |
| 相關次數： | 點閱：13 下載：0 |
| 分享至: |
| 查詢本校圖書館目錄 查詢臺灣博碩士論文知識加值系統 勘誤回報 |
人臉偵測與人臉辨識的研究已有超過廿年的歷史，各式各樣的相關應用也相繼的衍生出來。但在過去的人臉偵測與辨識研究中，都忽略了取像亮度因素對偵測及辨識結果的影響，也忽視了擷取特徵的準確度，以致於應用的成效不彰。在本論文的研究中，我們以多階分割 (multi-stage thresholding) 的技術及空間關係 (spatial relation) 的資訊來完成不受取像亮度因素影響的多人臉影像偵測及單人臉影像的精確特徵擷取。此外，我們的方法還可容忍人臉在三度空間中正負三十多度的旋轉。在多人臉影像偵測中，首先攝取一RGB彩色影像，轉換成VHS色譜影像，再依據HS色譜值來分割出人臉區域，最後再以型態學 (morphology) 運算修飾人臉區域。一個多階分割的方法是在人臉區域上分割出所有的特徵區塊，再以人臉五官的相對關係評估特徵區塊以判別人臉，最後再以邊線偵測法 (edge detection) 從最佳組合的特徵區塊中找出特徵點。
[1]Antoszczyszyn, M., M. Hannah, and Peter M. Grant, “Tracking of the motion of important facial features in model-based coding,” Signal Processing, Vol.66, No.2, pp.249-260, 1998.
[2]Brunelli, R. and T. Poggio, “Face recognition: features versus templates,” IEEE Trans. Pattern Analysis and Machine Intelligence, Vol.15, No.10, pp.1042-1052, 1993.
[3]Chellappa, R., C. Wilson, and S. Siroley, “Human and machine recognition of faces: A survey,” Proceedings of the IEEE, Vol.83, No.5, pp.705-740, 1995.
[4]Hunt., R. W. G., Measuring Color, John Wiley and Sons, 1989.
[5]Jeng, S. H., H. Y. Liao, Y. T. Liu and M. Y. Chern, “An efficient approach for facial feature detection using geometrical face model,” in Proc. 13th Int. Conf. Pattern Recognition, Vienna, Austria, Aug.25-29, 1996, pp.426-430.
[6]Juell, P. and R. Marsh, “A hierarchical neural network for human face detection,” Pattern Recognition, Vol.29, No.5, pp.781-787, 1996.
[7]Low, B. K. and M. K. Ibrahim, “A fast and accurate algorithm for facial feature segmentation,” in Proc. of Int. Conf. Image Processing, Oct.26-29, 1997, pp.518-521.
[8]Moghaddam, B. and A. Pentland, “An automatic system for model-based coding of faces,” in Proc. of Intl. Conf. Data Compression, USA, March.28-30, 1995, pp.362-370.
[9]Rowley, H. A., S. Baluja, and T. Kanade, “Neural network-based face detection,” IEEE Trans Pattern Analysis and Machine Intelligence, Vol.20, No.1, pp.23-28, 1998.
[10]Saber, E. and A. M. Tekalp, “Frontal-view face detection and facial feature extraction using color, shape and symmetry based cost functions,” Pattern Recognition Letters, Vol.19, No.8, pp.669-680, 1998.
[11]Shackleton, M. A. and W. J. Welsh, “Classification of facial features for recognition,” IEEE Computer Society Conference, June.3-6, 1991, pp.573-579.
[12]Sobottka, K. and I. Pitas, “Extraction of facial regions and features using color and shape information,” in Proc. 13th International Conference on Pattern Recognition, Vienna, Austria, Aug.25-29, 1996, pp.421-425.
[13]Sobottka, K. and I. Pitas, “A novel method for automatic face segmentation, facial feature extraction and tracking,” Signal Processing: Image Communication, Vol.12, No.3, pp.263-281, 1998.
[14]Turk, M. and A. Pentland, “Eigenfaces for recognition,” Journal of Cognitive Neuroscience, Vol.3, No.1, pp.71-86, 1991.
[15]Wang, J. and E. Sung, “Frontal-view face detection and facial feature extraction using color and morphological operations,” Pattern Recognition Letters, Vol.20, No.10, pp.1053-1068, 1999.
[16]Yanjiang, W. and Y. Baozong, “Segmentation method for face detection in complex background,” Electronics Letters, Vol.36, No.3, pp.213-214, 2000.
[17]Yow, K. and R. Cipolla, “Feature-based human face detection,” Image and Vision Computing, Vol.15, No.9, pp.713-735, 1997.
