Kinect's AI Breakthrough Explained

mikejuk writes "Microsoft Research has just published a scientific paper (PDF) and a video showing how the Kinect body tracking algorithm works — it's almost as impressive as some of the uses the Kinect has been put to. This article summarizes how Kinect does it. Quoting: '... What the team did next was to train a type of classifier called a decision forest, i.e. a collection of decision trees. Each tree was trained on a set of features on depth images that were pre-labeled with the target body parts. That is, the decision trees were modified until they gave the correct classification for a particular body part across the test set of images. Training just three trees using 1 million test images took about a day using a 1000-core cluster.'"

Comments

Strange Descriptions...

[Anonymous Coward]

- "What do you do for a living?"

- "I train trees to make a decision forest that can see human limbs."

- "Ah, I see. Makes sense. (WHAT THE FUCK???)"

Impressive.

[Chocolate Teapot]

Training just three trees using 1 million test images took about a day using a 1000-core cluster

Trees have traditionally been trained in Entish, which although reliable, is such an un-hasty language.