Steve
Zucker Computational Vision Group
Professor Steven W. Zucker
The Department of Computer Science
The Department of Electrical Engineering
Applied Mathematics Program
Interdepartmental Neuroscience Program
Center for Computational Vision and Control

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Research

Computational vision is at the heart of biomedicine and robotics, but is still quite primitive when compared with our own visual sense. We effortlessly demonstrate enormous flexibility and generality, which hides its staggering complexity: Nearly half of the primate brain processes visual information. Our group is attempting to put the requirements of vision systems together with insights from neurophysiology and the rigor of mathematics to develop an abstract theory of computational vision. Based on differential geometry, it leads to methods of curve detection and shading and texture analysis.

My group is working on early vision, grouping, and generic shape analysis. Recent projects and research topics are demonstrated below. For a recent overview paper on computing in cortical columns, a topic at the heart of our research, please click here.



Projects sampler

To view additional images, drag cursor over links (click on links for full size images).


Edge and Line Detection
( Details )
Original Image Detection Results
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Logical/Linear Edges
Canny
Logical/Linear Dark Lines
Logical/Linear Bright Lines

Texture Analysis
( Details )
Noisy initial measurements Relaxed Texture Flow
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Original Image
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Relaxation in Action
(please hold)

Shading Analysis
( Details )

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Shading flow field variance
Shading flow field (zoom)
Edge measurements
Edge classification
(white=fold, black=cut)

Stereo
( Details )

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Geometric Rectification
Initial edge tangents
Improved Space & Orientation quantization
3D Reconstruction

Color
( Details )

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Noisy Image
Relaxation in action

Computational neuroscience
( Details )

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Failure of existing models to predict statistics
Measured vs. Predicted statistics in the orientaiton domain
Bouton distribution image by Bosking et al. 1997

Psychophysics
( Details )
Which shape is different? Is the dot to the right of center?

Shock Graphs and Shape Matching
( Details )
Computed shocks Corresponding shock graph Matching via maximal subtree iosmorphism