Introduction to visual computing core concepts in computer vision, graphics, and image processing

Description

I FUNDAMENTALS Data Visualization Discretization Representation Noise Techniques Interpolation Geometric Intersections II IMAGE BASED VISUAL COMPUTING Convolution Linear Systems Linear Filters Implementation Details Spectral Analysis Discrete Fourier Transform Polar Notation Periodicity of Frequency Domain Aliasing Extension for 2D Interpretation Duality Feature Detection Edge Detection Feature Detection Other Non-Linear Filters III GEOMETRIC VISUAL COMPUTING Geometric Transformations Homogeneous Coordinates Linear Transformations Euclidean and A_ne Transformations Concatenation of Transformations Coordinate Systems Properties of Concatenation Projective Transformation Degrees of Freedom Non-Linear Transformations The Pinhole Camera The Model Considerations in the Practical Camera Epipolar Geometry Background Correspondences in Multi-View Geometry Fundamental Matrix Essential Matrix Recti_cation Applying Epipolar Geometry IV RADIOMETRIC VISUAL COMPUTING Light Radiometry Photometry and Color Color Reproduction Modeling Additive Color Mixtures Color Management Modeling Subtractive Color Mixture Limitations Photometric Processing Histogram Processing Image Composition Photometric Stereo V VISUAL CONTENT SYNTHESIS The Diverse Domain Modeling Processing Rendering Application Interactive Graphics pipeline Geometric Transformation of Vertices Clipping and Vertex Interpolation of Attributes Rasterization and Pixel Interpolation of Attributes Realism and Performance Illumination Shading Shadows Texture Mapping Bump Mapping Environment Mapping Transparency Accumulation Buffer Back Face Culling Visibility Culling Graphics Programming Development of Graphics Processing Unit Development of Graphics APIs and Libraries The Modern GPU and CUDA