OpenCV Haar Cascades
OpenCV Haar Cascades – PyImageSearch
“Haar cascades, first introduced by Viola and Jones in their seminal 2001 publication, Rapid Object Detection using a Boosted Cascade of Simple Features, are arguably OpenCV’s most popular object detection algorithm.
Sure, many algorithms are more accurate than Haar cascades (HOG + Linear SVM, SSDs, Faster R-CNN, YOLO, to name a few), but they are still relevant and useful today.
One of the primary benefits of Haar cascades is that they are just so fast — it’s hard to beat their speed.
The downside to Haar cascades is that they tend to be prone to false-positive detections, require parameter tuning when being applied for inference/detection, and just, in general, are not as accurate as the more “modern” algorithms we have today…”