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CSC3202: COMPUTER VISION

Core/Elective: Core Semester: 2 Credits: 4

Course Description

This course introduces concepts and applications in computer vision. Starting with image formation the course covers image processing methods such as filtering and edge detection, segmentation and classification. It includes vision tasks like; object detection, recognition and human motion detection. The content of the course also includes practical exercises to help the students formulating and solving computer vision problems.

Course Objectives

To understand processing of digital images
To familiarise different mathematical structures
To study detailed models of image formation
To study image feature detection, matching, segmentation and recognition
To understand classification and recognition of objects.
To familiarize state-of-the-art problems in computer vision

Course Content

1. Image formation –Geometric primitives and transformations – singular value decomposition – Harr,Walsh and Hadamard transforms – Discrete Fourier Transform - Photometric image formation – Statistical description of images.

2. Feature detection and matching – Digital morphology - Segmentation – Mean shift and mode finding – K-means and mixture of Gaussians – Graph cuts and energy-based methods – feature based alignment

3. Image restoration – Inverse filtering – Classification – Minimum distance classifiers – Cross validation – SVM – Ensembles – Bagging and boosting

4. Recognition – Object classification and detection – Face recognition – Instance recognition – Category recognition – Context and scene understanding – Human motion recognition

5. State-of-the-art and the future - Content based Search – Computation Photography - Image & video annotation

REFERNCES

1. Computer vision: Algorithms and Applications (1st Ed): Richard Szeliski , Springer (2010)
2. Algorithms for Image Processing and Computer Vision (2nd Ed): J. R. Parker, Wiley (2010)
3. Learning OpenCV: Computer Vision with the OpenCV Library (1st Ed): Gary Bradski, O’Reilly (2008)
4. Image Processing: The Fundamentals (2 edition): Maria Petrou and Costas Petrou, Wiley (2010)
5. Mathematical Elements of Computer Graphics (1st Ed): David F. Rogers and J. Alan Adams, McGraw Hill (1989)


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