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| layout | title | subtitle | description | excerpt | date | author | tags | categories | published | ||||
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| post | Deep Learning Haar Cascade Explained | 翻译 | 这是我认为最通俗易懂的 Haar 级联分类器的解释说明，文末视频非常形象。 | 2020-03-04 11:25:00 | Rick Chan |
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[原文连接]http://www.willberger.org/cascade-haar-explained/
Alright! This is where we start having some fun! The concept behind the Haar Cascade and how it is used in the real world is nothing short of amazing. So what is it?
Haar 级联分类器的背后思想以及其现实应用实在令人倍感惊奇。
Haar cascade
Haar Cascade is a machine learning object detection algorithm used to identify objects in an image or video and based on the concept of features proposed by Paul Viola and Michael Jones in their paper "Rapid Object Detection using a Boosted Cascade of Simple Features" in 2001.
Haar 级联分类器是一种机器学习算法，最初由 Paul Viola 和 Michael Jones 在 2001 年的论文《Rapid Object Detection using a Boosted Cascade of Simple Features》中提出。该算法能够通过特征来识别图像或视频中的物体。
参考资料
人脸检测之Haar分类器
What’s the Difference Between Haar-Feature Classifiers and Convolutional Neural Networks?
Computer Vision — Detecting objects using Haar Cascade Classifier
Deep Learning Haar Cascade Explained
浅析人脸检测之Haar分类器方法：Haar特征、积分图、AdaBoost、级联