Syllabus Computer Vision - (3171614) CreditsExamination MarksTotal Marks CTheory MarksPractical Marks ESE (E)PAESE (V)PA (I) 470303020150 1.Overview of computer vision and its applications : Image Formation and Representation : Imaging geometry, radiometry, digitization, cameras and Projections, rigid and affine transformation. (Chapter - 1) 2.Image Processing : Pixel transforms, color transforms, histogram processing, histogram equalization, filtering, convolution, Fourier transformation and its applications in sharpening, blurring and noise removal. (Chapter - 2) 3.Feature detection : Edge detection, corner detection, line and curve detection, active contours, SIFT and HOG descriptors, shape context descriptors, Morphological operations. (Chapter - 3) 4.Segmentation : Active contours, split & merge, watershed, region splitting, region merging, graph-based segmentation, mean shift and model finding, Normalized cut. (Chapter - 4) 5.Camera calibration : Camera models; intrinsic and extrinsic parameters; radial lens distortion; direct parameter calibration; camera parameters from projection matrices; orthographic, weak perspective, affine, and perspective camera models. (Chapter - 5) 6.Motion representation : The motion field of rigid objects; motion parallax; optical flow, the image brightness constancy equation, affine flow; differential techniques; feature-based techniques; regularization and robust estimation. (Chapter - 6) 7.Motion tracking : Statistical filtering; iterated estimation; observability and linear systems; the Kalman filter. (Chapter - 7) 8.Object recognition and shape representation : Alignment, appearance-based methods, invariants, image eigenspaces. (Chapter - 8)
