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Fast Face Detection Based on Walsh Feature and Enhanced Cascade Algorithm


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Fast Face Detection Based on Walsh Feature and Enhanced Cascade Algorithm
GUO Zhi-bo12YAN Yun-yang1YANG Jing-yu1
1.School of Information Engineering,Yangzhou University,Yangzhou 225009,China;2.School of Computer Science and Technology,NUST,Nanjing 210094,China
Walsh feature AdaBoost enhanced Cascade face detection
The training time cost is very expensive when mass Haar-Like features are used to obtain the face detector based on AdaBoost and Cascade algorithm.The paper presents a Walsh feature to replace Haar-Like feature in the training process,which can decrease the redundancy among the features and save the training time and memory.Aiming at the shortage of entirely inheriting prior classifiers in the Nesting Cascade algorithm,an enhanced Cascade algorithm that has independence characteristic and inheritance speciality is proposed.The experimental results from MIT-CBCL database show that the Walsh feature can accelerate the training process and the enhanced Cascade algorithm can increase the test precision.A trained face detector is used to detect faces in the MIT+CMU test set,and the detected results demonstrate that the proposed algorithm is more effective than other correlative methods.


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Last Update: 2012-12-05