Course Contents
Computer Vision is the branch of Computer Science whose goal is to recognize objects from digital images. These images can be acquired using still and video cameras, infrared cameras, radars, or specialized sensors. Topics include image processing; segmentation, grouping, and boundary detection; recognition and detection; motion estimation and structure from motion.
Course Synopsis
The course will give the understanding of the physics of image formation; the geometry of computer vision (stereo reconstruction and tracking); and statistical methods for detection and classification.
Course Learning Outcomes
Students will be able to :
• Understand how computers understand the visual world of humans.
• Treat vision as a process of inference from data.
• Recognize various visual phenomena.
Filtering
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Edge Detection
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Face Detection History, basic models, face detection using Haar Cascades in the context of a Viola-Jones object detection framework trained to identify images via AdaBoost algorithm.
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Face Recognition, Eigen Face
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Appearance models, Deformable image registration, training data: image correspondences, aligning sets of image correspondences, Principal component analysis (PCA), Fitting shape models, Active shape model algorithm
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Local Image Features, interest point detection, Harris corner detector
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Image Synthesis, Image transformations, SIFT
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Warping
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Morphing
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Image registration / stiching, identifying common control points on two maps, transformation models, estimating the transformation parameters, performing geometric transformation
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Reconstructing 3-D scene information basics, 8 point algorithm, Epipolar geometry
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Structure from motion
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Camera Model and Caliberation
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Optical Flow
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Motion Model
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Introduction
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Image formation and coordinate systems
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Field of View Example
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Pixel to 3D Unit Vector Example
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Camera Parameters
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Sampling and Quantization
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White Balance
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Book Title : Computer Vision: A Modern Approach,
Author : D. Forsyth, and J. Ponce
Edition :
Publisher : Prentice Hall
Book Title : Computer Vision: Algorithms and Applications
Author : R. Szeliski
Edition :
Publisher : Springer
Book Title : Multiple View Geometry in Computer Vision
Author : R. Hartley and A. Zisserman
Edition : 2nd Ed
Publisher : Cambridge University Press
Book Title : Robot Vision
Author : B.K.P. Horn
Edition :
Publisher : MIT Press
Book Title : An Invitation to 3D Vision: From Images to Geometric Models
Author : Ma, Soatto, Kosecka, Sastry
Edition :
Publisher : Springer Verlag
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