Stereo vision may indeed be a leap ahead for computers, but there's still a long way to go before machines can achieve the sophistication of human sight. "Because vision comes so naturally to us, we don't appreciate the problem intuitively," said David Touretzky, a computational neuroscientist at Carnegie Mellon. "I don't think we got that appreciation until people started trying to build computer systems to see." A large fraction of the brains of primates such as monkeys, apes and humans is devoted to processing visual information, Touretzky said. There are more than 20 different specialised areas for tasks such as recognizing motion, color, shapes and spatial relationships between objects. "These areas are all interconnected in ways not fully understood yet," Touretzky said, but together these parts of the brain can discern the difference between the edge of a shadow and the edge of an object or compensate for color shifts that occur when the sun comes out. Tyzx isn't the only company trying to capitalize on stereo computer vision. Microsoft Research is working on technology that extracts 3D information from 2D pictures. Point Grey Research already has cameras on the market, though its processing algorithms require a full-fledged computer. In Japan, a company called ViewPlus is working in collaboration with Point Grey Research. Its products, though, combine as many as 60 cameras into a spherical system that produces 20 simultaneous video information streams. These other companies are taking a fundamentally different approach to Tyzx in one respect: Their systems compare more than two images. Carnegie Mellon's Kanade said it might seem that comparing three images would be a harder computational task, but in fact having more data to work with can actually make the process simpler. DeepSea processing
The key development at Tyzx is its custom chip, which runs an algorithm called census correspondence that quickly finds similarities across two streams of video images broken up into a square grid of 512 pixels, or picture elements. The chip can perform this comparison 125 times per second with a video image measuring 512 by 512 pixels, but the 33MHz DeepSea consumes much less power than full-fledged processors such as Intel's Pentium. "It allows incredibly compute-intensive searching for matching pixels to happen very fast at a very low price. It allows us to bring stereo vision to computers," chief executive Buck said. Another important development needed to reach Tyzx's low-price targets is camera sensors built using the comparatively inexpensive complimentary metal-oxide semiconductor (CMOS) technology -- the same process used to build most computer chips, Buck said. Digital cameras today use more elaborate -- but more expensive -- "charge-coupled devices", or CCDs. Kanade has an appreciation for the difficulties involved. About 10 years ago he built an expensive but pioneering stereo vision system with many processors that could determine range information by comparing the images from multiple cameras. Since then, more powerful computer processing abilities have elevated the potential of the field, which Kanade believes will take off once stereo cameras are as cheap as today's ordinary video cameras. "I'm very impressed with the various attempts which made real-time stereo possible. I think the Tyzx effort may be one of the eventual successes," Kanade said.
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