OpenCV - Extract Features or use Haar training

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I am currently working on a Project to detect a Chessboard and also the position of the figures. After taking a photo, the App should scan for known figures (pawn etc.). My Question: I found two methods of detecting known Objects in an image.

1. Extract features from one image and search for same features in a second image (Features2D + Homography to find a known object)
2. Search for known Objects using Haar cascades (Cascade Classifier Training)

I don't know which of these methods is more reliable. Can I use the Homography to detect multiple objects in one image?

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