Guys… Have we learned nothing?
Rain check on taking that look at iWork as planned.
Using any Office suite on Mac OS X is hell.
- Sony Vaio: Resistance Edition, i.e. technology far superior anything we’ve seen in the flash-forwards in the previous movies. I mean, isn’t humanity supposed to outnumbered and on the brink of extinction? Wouldn’t a military base be an easy target for Skynet? Also, 14 years have passed since the planet was nuked, but they still have helicopters, jets, high-tech equipment, ammunition, laboratories, and the equipment and skill to perform heart transplants?
- Common, and if that’s not enough: Common with sunglasses at night.
- GUIs that can be interacted with by humans at Skynet. Well, GUIs at Skynet in general.
- The fact that Skynet are trying to kill John Connor and Kyle Reese before they have any idea who they are and what they will do.
- Terminators with headbands.
The test system was an ordinary Xbox 360, connected to small PC and camera that simulates the final Natal rig. There are two cameras—one RGB, for face recognition and display video, and one infrared, for tracking movement and depth. Why infrared? The eye doesn’t see infrared light. And when you combine an infrared camera with an infrared emitter (also part of Natal), a room is flooded with a spectrum of invisible light that works in the dark.
The 3D sensor itself is a pretty incredible piece of equipment providing detailed 3D information about the environment similar to very expensive laser range finding systems but at a tiny fraction of the cost. Depth cameras provide you with a point cloud of the surface of objects that is fairly insensitive to various lighting conditions allowing you to do things that are simply impossible with a normal camera.
But once you have the 3D information, you then have to interpret that cloud of points as “people”. This is where the researcher jaws stay dropped. The human tracking algorithms that the teams have developed are well ahead of the state of the art in computer vision in this domain. The sophistication and performance of the algorithms rival or exceed anything that I’ve seen in academic research, never mind a consumer product. At times, working on this project has felt like a miniature “Manhattan project” with developers and researchers from around the world coming together to make this happen.