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MIT reports new insights in visual recognition

CAMBRIDGE, Mass.--MIT scientists are reporting new insights into how the human brain recognizes objects, especially faces, in work that could lead to improved machine vision systems, diagnostics for certain neurological conditions and more.

Look at a photo of people running a marathon. The lead runners' faces are quite distinct, but we can also make out the faces of those farther in the distance. Zoom in on that distant runner, however, "and you'll see that there's very little intrinsic face-related information, such as eyes and a nose. It's just a diffuse blob. Yet somehow we can classify that blob as a face," said Pawan Sinha, an assistant professor in the Department of Brain and Cognitive Sciences (BCS). In contrast, performing this task reliably is beyond even the most advanced computer-recognition systems.

In the April 2 issue of Science, Sinha and colleagues show that a specific brain region known to be activated by clear images of faces is also strongly activated by very blurred images, just so long as surrounding contextual cues (such as a body) are present. "In other words, the neural circuitry in the human brain can use context to compensate for extreme levels of image degradations," Sinha said.

Past studies of human behavior and the work of many artists have suggested that context plays a role in recognition. "What is novel about this work is that it provides direct evidence of contextual cues eliciting object-specific neural responses in the brain," Sinha said.

The team used functional magnetic resonance imaging to map neuronal responses of the brain's fusiform face area (FFA) to a variety of images. These included clear faces, blurred faces attached to bodies, blurred faces alone, bodies alone, and a blurred face placed in the wrong context (below the torso, for example).

Only the clear faces and blurred faces with proper contextual cues elicited strong FFA responses. "These data support the idea that facia
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Contact: Elizabeth Thomson
thomson@mit.edu
617-258-5402
Massachusetts Institute of Technology
1-Apr-2004


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