透過您的圖書館登入
IP:18.221.222.47
  • 學位論文

達更大偵測範圍的改良人臉偵測系統

A Modified Face Detection System with Wider Detection Range

指導教授 : 陳永昌

摘要


在現今的電腦視覺科技中,人臉偵測是一項重要的技術,可以應用在安全監控系統或機器人視覺上。因此快速且準確的找出影像中的各個人臉,是最重要的目標。Viola和Jones在2001年提出了一套技術,由大量收集的人臉樣本分析其規則性,可以快速偵測各類圖像中的人臉。但是由於樣本都是採用正面的臉來訓練,因此對於其他角度的人臉,Viola和Jones的方法並不適用。 這篇論文,我們提出一套方法可以使viola-jones偵測器達到更大的偵測範圍。方法包括三個步驟:膚色萃取、尋找眼睛候選區域、viola-jones偵測器。一張測試影像進來,不同大小的視窗在各處試著尋找人臉。視窗經過膚色萃取後,若含超過一半的膚色點,才會繼續往下做,否則就直接視為非人臉。第二階段是尋找眼睛候選,若有眼睛候選的邊緣密集特性,才更有可能是人臉,可繼續第三階段的處理。我們計算出眼睛候選偏轉的角度,經過旋轉矩陣,把非正面的臉,轉成正面。最後交給viola-jones偵測器篩選出人臉。 在實驗結果中,跟傳統的viola-jones偵測器相比,我們的方法在兩種轉動方式中都有很好的表現,可以找到更大角度偏轉(RIP)和側轉(ROP)的臉。而我們拿新聞照片當測試圖片,我們的方法不僅達到更大的偵測範圍,並且減少了錯誤的發生。雖然增加了處理步驟,但是我們的一些加速技巧,使偵測時間仍在可接受的範圍內。如果測試影響圖不大,而且膚色萃取效果佳的情況下,處理時間可小於一秒。

並列摘要


Face detection is a more and more important topic nowadays. Because of the need on machine vision and surveillance system, we have to let a computer detect the faces in a picture rapidly and accurately. Viola and Jones [1] proposed a rapid and robust method, but it is just suitable for a frontal and upright face. Detecting multi-view faces is also a discussed problem today. In this thesis, a face detection system applicable for wider range is proposed. It contains analyzing the face pose, rotating the face back, and applying the traditional viola-jones detector. First, we search for potential face regions by performing skin-color detection. From these skin-color blocks, check if there is a pair of eyes inside and preserve window candidates that are much like faces. Second, according to the result of the pair of eyes candidate, we choose the angle to rotate each face candidate to frontal and upright face. Finally, the rotated face candidate is computed by viola-jones detector to judge whether it is a genuine face or not. In the experiment, our method extends the detection range of rotation-off-plane (ROP) and rotation-in-plane (RIP) face. Some faces, including profiled and rotated faces, that can not be detected by original viola-jones face detector are detected by our modified face detector with complemented pre-processing. The processing time is also acceptable. Especially for simple and small size images, it can achieve nearly real-time.

參考文獻


[1] P. Viola and M. Jones, “Rapid Object Detection using a Boosted Cascade of Simple Features”, IEEE Conference on Computer Vision and Pattern Recognition, vol. 1, pp. 511-518, 2001
[2] G. Yang and T. S. Huang, “Human Face Detection in Complex Background”, Pattern Recognition, vol. 27, no. 1, pp. 53-63, 1994
[4] K. C. Yow and R. Cipolla, “Enhancing Human Face Detection Using Motion and Active Contours”, Proc. Third Asian Conference Computer Vision, pp. 515-522, 1998
[7] E. Osuna, R. Freund, F. Girosi, “Training Support Vector Machines: An Application to Face Detection”, Proc. IEEE Conference on Computer Vision and Pattern Recognition, pp. 130-136, 1997
[8] H. Schneiderman and T. Kanade, “Probabilistic Model of Local Appearance and Spatial Relationships for Object Recognition”, Proc. IEEE Conf. Computer Vision and Pattern Recognition, pp. 45-51, 1998

被引用紀錄


孔繁傑(2013)。利用視訊與聲訊雙重處理進行說話者位置偵測〔碩士論文,國立清華大學〕。華藝線上圖書館。https://doi.org/10.6843/NTHU.2013.00780
林縈婕(2009)。立法院女性從業人員運動行為及運動介入成效之研究〔碩士論文,國立臺灣師範大學〕。華藝線上圖書館。https://www.airitilibrary.com/Article/Detail?DocID=U0021-1610201315165254

延伸閱讀