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Research and Design of Face Detection Based on OpenCV in CodeBlocks

机译:基于OpenCV在CodeBlocks中的脸部检测研究与设计

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To implement the problem that the side face detector is slow and its detection rate is low, in this paper, we choose the Adaboost face detection algorithm based on statistics. Then the characteristics of imaging processing software OpenCV and the principle and training flow of Adaboost face detector are introduced. Further, combination with the supplement Haar-like features improved, the full range of face detection based on OpenCV in CodeBlocks is achievement, thereby decreasing the loss of the human faces.
机译:为了实现侧面检测器慢速且其检测率低的问题,本文选择了基于统计的Adaboost面部检测算法。然后,介绍了成像处理软件OpenCV的特征和Adaboost面部检测器的原理和训练流。此外,与补充哈尔样特征的组合改善,基于CodeBlocks的OpenCV的全方位检测是成就,从而降低了人面的损失。

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