3.06.2007

Object Recognition: MIT Scientists Demo Cool Virtual Brain Technology
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Object Recognition: MIT scientists have applied a computer model of how the brain processes visual information to a complex, real-world task: recognizing the objects in a busy street scene.



A couple of years ago I saw the same kind of demo at Redwood Neuroscience Institute, Jeff Hawkins' Neuroscience gathering. The demo concerned a street scene in Italy. The institute has moved over to Berkeley - instead Numenta, Hawkins' latest start-up has taken its place. This kind of object recognition is quite a bit different from cognitivelabs.com, in case you're wondering - numenta is kind of a successor to machine vision - rather than chronometrics, defined as "nerve conduction velocity" by Arthur Jensen, which could be considered a measure of the human OS relative to silicon/network mediation and also is sensitive to genetic factors. (see the latest Cognitive Labs' paper: advance abstract here)

..."People have been talking about computers imitating the brain for a long time," said Tomaso Poggio, the Eugene McDermott professor of brain and cognitive sciences and a member of the McGovern Institute for Brain Research at MIT. "Our work is biologically inspired computer science," said Poggio.

"We developed a model of the visual system that was meant to be useful for neuroscientists in designing and interpreting experiments but that also could be used for computer science," said Thomas Serre, a postdoctoral associate in Poggio's lab and lead author of a paper on the work in the March 2007 IEEE Transactions on Pattern Analysis and Machine Intelligence."We chose street-scene recognition as an example because it has a restricted set of object categories, and it has practical social applications," said Serre. The IEEE paper describes how the team "showed" the model randomly selected images so that it could "learn" to identify commonly occurring features in real-word objects such as trees and people. In so-called supervised training sessions, the model used those features to label by category examples of objects found in digital photographs of street scenes, such as buildings and cars.

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