Vision scientists have made significant progress in understanding how humans detect a single stimulus, but they know much less about how we process complex scenes consisting of multiple stimuli. At present, there is considerable evidence that the visual system analyzes the visual scene using local mechanisms tuned for specific stimulus properties such as size, orientation, and direction of motion. However, there is still no clear understanding of how all of these different local components are recombined to synthesize an apparently seamless visual scene. We approach this problem by working at a level that is intermediate in complexity between single stimuli and complex scenes. Our interest is in the ability of human observers to combine information from multiple stimuli across space and time. Can the ability to process multiple stimuli be predicted from what is known about the processing of single stimuli?

This research can be classified into two broad categories: studies of visual search, and of visual motion processing. In visual search, we are interested in understanding the general problem of search, namely how do we find a particular piece of paper on a cluttered desktop or find a friend in a crowd. A typical laboratory task involves finding a line of a particular orientation among shorter lines of random orientation. The real world equivalent of this task might be finding a needle in a haystack. What is most interesting is that the human visual system appears to combine the information from multiple detectors in a manner that is close to the best performance that can be achieved.

In the area of visual motion processing, we have shown that current ideas about single motion detectors can explain our ability to see brief motion, e.g. a spot moving along a short trajectory. However, when the motion trajectory is extended, as is typically the case in real life, human performance far exceeds that of individual motion detectors acting independently. Our research into how local motion information is combined along a smooth motion path indicates that the visual system uses a predictive strategy: Detectors early in the motion sequence cue others later in the sequence that a motion stimulus is headed their way. Furthermore, our current work shows that this cueing strategy also helps organize local oriented segments into smooth contours and may thus be a general-purpose way to detect smoothly varying signals in clutter.

For more information, visit Preeti Verghese's lab web pages.

Collaborators: M. Concetta Morrone, Stefano Baldassi, David C. Burr, Douglas Taylor. Dennis Levi, Suzanne P. McKee, Anna Ma-Wyatt, James Coughlan, Laura Renninger.