A fast face detection method for illumination variant condition

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題名:	A fast face detection method for illumination variant condition
作者:	Hsia, C.-H. Chiang, J.-S. Lin, C.-Y.
貢獻者:	電機系
關鍵詞:	Illumination variant face detection Adaboost Neural network Modified census transform Real-time detection
日期:	2015
上傳時間:	2016-03-10 14:54:06 (UTC+8)
摘要:	General boosting algorithms for face detection use rectangular features. To obtain a better performance, it needs more training samples and may generate an unpredictable number of features. Besides using pixel values, which are easily affected by illumination, to calculate the rectangular features, it usually needs to preprocess the data before calculating the values of the features. Such an approach may increase computation time. To overcome the drawbacks, we propose a new solution based on the Adaboost algorithm and the Back Propagation Network (BPN) of a Neural Network (NN), combining local and global features with cascade architecture to detect human faces. We use the Modi fied Census Transform (MCT) feature, which belongs to texture features and is less sensitive to illumination, for local feature calculation. In this approach, it is not necessary to preprocess each sub-window of the image. For classification, we use the structure of the hierarchical feature to control the number of features. With only MCT, it is easy to misjudge faces and, therefore, in this work, we include the brightness information of global features to eliminate the False Positive (FP) regions. As a result, the proposed approach can have a Detection Rate (DR) of 99%, an FPs of only 11, and detection speed of 27.92 Frames Per Second (FPS). (C) 2015 Sharif University of Technology. All rights reserved.
關聯:	SCIENTIA IRANICA 卷: 22 期: 6 頁碼: 2081-2091
顯示於類別:	[電機工程系] 期刊論文

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