6.801 Machine Vision

Class Info

Deriving a symbolic description of the environment from an image. Understanding physics of image formation. Image analysis as an inversion problem. Binary image processing and filtering of images as preprocessing steps. Recovering shape, lightness, orientation, and motion. Using constraints to reduce the ambiguity. Photometric stereo and extended Gaussian sphere. Applications to robotics; intelligent interaction of machines with their environment. Students taking the graduate version complete different assignments.

This class has 6.003 as a prerequisite.

6.801 will be offered this semester (Fall 2017). It is instructed by B. K. P. Horn.

Lecture occurs 9:30 AM to 11:00 AM on Tuesdays and Thursdays in 32-124.

This class counts for a total of 12 credits.

You can find more information on MIT OpenCourseWare at the Machine Vision site or on the 6.801 Stellar site.

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