Category Archives: Decision forests

Decision Forests

forestDecision Forests¬†(also called random trees, random forests etc) are a machine learning system that can be applied to many tasks including image recognition. What’s nice is that software is available here, OpenCV has an implementation and there’s also a GPU implementation¬†along with no doubt many others. The image shows one of the examples using the Microsoft code where the forest has learned the classification of a spiral pattern. This paper describes a very interesting project using multiple layers of decision forests to determine depth using reflected near IR illumination intensity so that an (almost) standard webcam can recover depth information for things like gesture recognition. The nice thing is that the sensor can be very small and processing overhead is very low.