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CS 231A: Computer Vision: From 3D Reconstruction to Recognition

(Formerly 223B) An introduction to the concepts and applications in computer vision. Topics include: cameras and projection models, low-level image processing methods such as filtering and edge detection; mid-level vision topics such as segmentation and clustering; shape reconstruction from stereo, as well as high-level vision tasks such as object recognition, scene recognition, face detection and human motion categorization. Prerequisites: linear algebra, basic probability and statistics.
Terms: Win | Units: 3-4 | Grading: Letter or Credit/No Credit
Instructors: Savarese, S. (PI)

CS 231M: Mobile Computer Vision

The course surveys recent developments in computer vision, graphics and image processing for mobile application. Topics of interest include: feature extraction, image enhancement and digital photography, 3D scene understanding and modeling, virtual augmentation, object recognition and categorization, human activity recognition. As part of this course, students will familiarize with a state-of-the-art mobile hardware and software development platform: an NVIDIA Tegra-based Android tablet, with relevant libraries such as OpenCV and FCam. Tablets will be available for each student team. Prerequisites: Knowledge of linear algebra, probability, as well as concepts introduced in either CS131A or CS231A and CS232 (or equivalent) are necessary for understanding the material covered in this class. C++ (or Java) programming experience is expected.
Terms: Spr | Units: 3-4 | Grading: Letter or Credit/No Credit
Instructors: Savarese, S. (PI)
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