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We describe a method for visual object detection based on an ensemble ofoptimized decision trees organized in a cascade of rejectors. The trees usepixel intensity comparisons in their internal nodes and this makes them able toprocess image regions very fast. Experimental analysis is provided through aface detection problem. The obtained results are encouraging and demonstratethat the method has practical value. Additionally, we analyse its sensitivityto noise and show how to perform fast rotation invariant object detection.Complete source code is provided at https://github.com/nenadmarkus/pico.

Object Detection with Pixel Intensity Comparisons Organized in Decision Trees