OpenCV Haar Cascades

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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…”

Source: www.pyimagesearch.com/2021/04/12/opencv-haar-cascades/

April 13, 2021
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