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