High-Level Vision

Humans recognize visual objects with such ease that it is easy to overlook what an impressive computational feat this represents. Any given object in the world can cast an effectively infinite number of different images onto the retina, depending on its position relative to the viewer, the configuration of light sources, and the presence of other objects in the visual field. In spite of this extreme variation, biological visual systems are able to effortlessly recognize at least hundreds of thousands of distinct object classes—a feat that no current artificial system can come close to achieving.

Our Research

Our laboratory seeks to understand the computational underpinnings of object recognition through a concerted effort on two fronts. First, we endeavor to understand the workings of biological visual systems using a variety of experimental techniques, ranging from microelectrode recordings to visual psychophysics. Second, we attempt to instantiate what we have learned into artificial object recognition systems, leveraging recent advances in parallel computing to build systems that begin to approach the scale of natural systems. By combining reverse- and forward-engineering approaches, we hope to accelerate progress in both domains.

About The Rowland Institute

The Rowland Institute at Harvard is dedicated to experimental science over a broad range of disciplines. Current research is carried out in physics, chemistry, and biology, with an emphasis on interdisciplinary work and the development of new experimental tools. The Institute is located in Cambridge, Massachusetts near the Longfellow Bridge, a few miles downstream from the main campus.

Some current projects


Reverse Engineering the Visual System

Advanced Tools for Electrode Placement

A Self Calibrating Eye-Tracker

Large-scale Face Recognition
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