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AD-701 · AI for Computer Vision/Official Syllabus

AI for Computer Vision (AD-701) - Official Syllabus

1
Unit 1

Introduction to Image Formation and Processing

  • Computer Vision
  • Geometric primitives
  • Geometric transformations
  • Photometric image formation
  • Digital camera
  • Point operators
  • Linear filtering
  • More neighborhood operators
  • Fourier transforms
  • Pyramids
  • Wavelets
  • Global optimization
2
Unit 2

Feature Detection, Matching and Segmentation

  • Points and patches
  • Edges
  • Lines
  • Segmentation
  • Active contours
  • Split and merge
  • Mean shift and mode finding
  • Normalized cuts
  • Graph cuts and energy-based methods
3
Unit 3

Feature-based Alignment & Motion Estimation

  • 2D feature-based alignment
  • 3D feature-based alignment
  • Pose estimation
  • Geometric intrinsic calibration
  • Triangulation
  • Two-frame structure from motion
  • Factorization
  • Bundle adjustment
  • Constrained structure and motion
  • Translational alignment
  • Parametric motion
  • Spline-based motion
  • Optical flow
  • Layered motion
4
Unit 4

3D Reconstruction

  • Shape from X
  • Active range finding
  • Surface representations
  • Point-based representations
  • Volumetric representations
  • Model-based reconstruction
  • Recovering texture maps
  • Albedos
5
Unit 5

Image-based Rendering and Recognition

  • View interpolation
  • Layered depth images
  • Light fields and Lumigraphs
  • Environment mattes
  • Video-based rendering
  • Object detection
  • Face recognition
  • Instance recognition
  • Category recognition
  • Context and scene understanding
  • Recognition databases and test sets

Laboratory Experiments

  • OpenCV Installation and working with Python
  • Basic Image Processing, loading images, Cropping, Resizing, Thresholding, Contour analysis, Blob detection
  • Image Annotation - Drawing lines, text circle, rectangle, ellipse on images
  • Image Enhancement, Understanding Color spaces, color space conversion, Histogram equalization, Convolution, Image smoothing, Gradients, Edge Detection
  • Image Features and Image Alignment - Image transforms - Fourier, Hough, Extract ORB Image features, Feature matching and cloning
  • Feature matching based image alignment
  • Image segmentation using Graphcut / Grabcut
  • Camera Calibration with circular grid
  • Pose Estimation
  • 3D Reconstruction - Creating Depth map from stereo images

Reference Books

  • Multiple View Geometry in Computer Vision — Richard Hartley, Andrew Zisserman
  • Pattern Recognition and Machine Learning — Christopher M. Bishop
  • Computer and Machine Vision — E. R. Davies
  • Computer Vision: Algorithms and Applications — Richard Szeliski
  • Computer Vision: A Modern Approach — D. A. Forsyth, J. Ponce
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