ehtml> CS491Y/691Y: Computer Vision Topics

Computer Science & Engineering Department

CS491Y/691Y Computer Vision Topics

  • Meets: MW 4:00pm - 5:15pm (SEM 234)

  • Instructor: Dr. George Bebis

  • Prerequisites

    Background in image processing (CS474/674), computer vision (CS485/685), pattern recognition (CS479/679), linear algebra, probabilities, and statistics.


    No text is required in this course; all material will be drawn from research papers.

    Useful Texts

    Computer Vision resources

    Object Recognition Datasets

    Useful Software

    Description and Objectives

    Interest point detectors and descriptors are now at the core of many Computer Vision applications such as object recognition, 3D reconstruction, image retrieval and camera localization. The purpose of this course is to review recent advances in this important area by discussing research papers and attending video lectures. The course is intended for students interested in computer vision research. Good background in computer vision, linear algebra, probability, statistics, and calculus are required.


    Schedule of Presentations

    Video Lectures

    [VL10] Compressive Sensing for Computer Vision: Hype vs Hope (Rama Chellappa, Univ of Maryland) (58 min)

    Local Detectors and Descriptors


    Department of Computer Science & Engineering, University of Nevada, Reno, NV 89557
    Page created and maintained by: Dr. George Bebis (