Table of Contents

Original Table of Contents

1 - Computer vision issues

1.1 - Achieving simple vision goals (pg 1)
1.2 - High-level and low-level capabilities (pg 2)
1.3 - A range of representations (pg 6)
1.4 - The role of computers (pg 9)
1.5 - Computer vision research and applications (pg 12)

2 - Image Formation

2.1 - Images (pg 4)

2.2 - Image Model (pg 1)

2.2.1 - Image Functions (pg 1)
2.2.2 - Imaging Geometry (pg 2)
2.2.3 - Reflectance (pg 5)
2.2.4 - Spatial Properties (pg 7)
2.2.5 - Color (pg 14)
2.2.6 - Digital Images (pg 18)

2.3 - Imaging Devices for Computer Vision (pg 1)

2.3.1 - Photographic Imaging (pg 3)
2.3.2 - Sensing Range (pg 11)
2.3.3 - Reconstruction Imaging (pg 15)

3 - Early Processing

3.1 - Recovering Intrinsic Structure (pg 1)

3.2 - Filtering the Image (pg 3)

3.2.1 - Template Matching (pg 3)
3.2.2 - Histogram Transformations (pg 8)
3.2.3 - Background Subtraction (pg 10)
3.2.4 - Filtering and Reflectance Models (pg 11)

3.3 - Finding Local Edges (pg 1)

3.3.1 - Types of Edge Operators (pg 2)
3.3.2 - Edge Thresholding Strategies (pg 6)
3.3.3 - Three-Dimensional Edge Operators (pg 7)
3.3.4 - How Good Are Edge Operators? (pg 9)
3.3.5 - Edge Relaxation (pg 11)

3.4 - Range Information from Geometry (pg 1)

3.4.1 - Stereo Vision and Triangulation (pg 1)
3.4.2 - A Relaxation Algorithm for Stereo (pg 2)

3.5 - Surface Orientation from Reflectance Models (pg 6)

3.5.1 - Reflectivity Functions (pg 6)
3.5.2 - Surface Gradient (pg 8)
3.5.3 - Photometric Stereo (pg 11)
3.5.4 - Shape from Shading by Relaxation (pg 12)

3.6 - Optical Flow (pg 1)

3.6.1 - The Fundamental Flow Constraint (pg 1)
3.6.2 - Calculating Optical Flow by Relaxation (pg 2)

3.7 - Resolution Pyramids (pg 5)

3.7.1 - Gray-Level Consolidation (pg 5)
3.7.2 - Pyramidal Structures in Correlation (pg 6)
3.7.3 - Pyramidal Structures in Edge Detection (pg 8)

4 - Boundary Detection

4.1 - On Associating Edge Elements (pg 4)

4.2 - Searching Near an Approximate Location (pg 6)

4.2.1 - Adjusting A Priori Boundaries (pg 6)
4.2.2 - Non-Linear Correlation in Edge Space (pg 6)
4.2.3 - Divide-and-Conquer Boundary Detection (pg 7)

4.3 - The Hough Method for Curve Detection (pg 1)

4.3.1 - Use of the Gradient (pg 2)
4.3.2 - Some Examples (pg 3)
4.3.3 - Trading Off Work in Parameter Space for Work in Image Space (pg 4)
4.3.4 - Generalizing the Hough Transform (pg 6)

4.4 - Edge Following as Graph Searching (pg 1)

4.4.1 - Good Evaluation Functions (pg 3)
4.4.2 - Finding All the Boundaries (pg 3)
4.4.3 - Alteratives to the A Algorithm (pg 6)

4.5 - Edge Following as Dynamic Programming (pg 1)

4.5.1 - Dynamic Programming (pg 1)
4.5.2 - Dynamic Programming for Images (pg 3)
4.5.3 - Lower Resolution Evaluation Functions (pg 5)
4.5.4 - Theoretical Questions about Dynamic Programming (pg 7)

4.6 - Contour Following (pg 7)

4.6.1 - Extension to Gray-Level Images (pg 8)
4.6.2 - Generalization to Higher-Dimensional Image Data (pg 10)

5 - Region Growing

5.1 - Regions (pg 1)

5.2 - A Local Technique: Blob Coloring (pg 3)

5.3 - Global Techniques: Region Growing via Thresholding (pg 4)

5.3.1 - Thresholding in Multidimensional Space (pg 5)
5.3.2 - Hierarchical Refinement (pg 7)

5.4 - Splitting and Merging (pg 7)

5.4.1 - State-Space Approach to Region Growing (pg 9)
5.4.2 - Low-Level Boundary Data Structures (pg 10)
5.4.3 - Graph-Oriented Region Structures (pg 11)

5.5 - Incorporation of Semantics (pg 12)

6 - Texture

6.1 - What is Texture? (pg 1)

6.2 - Texture Primitives (pg 4)

6.3 - Structural Models of Texel Placement (pg 5)

6.3.1 - Grammatical Models (pg 7)
6.3.2 - Shape Grammars (pg 8)
6.3.3 - Tree Grammars (pg 10)
6.3.4 - Array Grammars (pg 13)

6.4 - Texture as a Pattern Recognition Problem (pg 1)

6.4.1 - Texture Energy (pg 4)
6.4.2 - Spatial Gray-Level Dependence (pg 6)
6.4.3 - Region Texels (pg 8)

6.5 - The Texture Gradient (pg 9)

7.1 - Motion Understanding (pg 1)

7.1.1 - Domain-Independent Understanding (pg 2)
7.1.2 - Domain-Dependent Understanding (pg 2)

7.2 - Understanding Optical Flow (pg 5)

7.2.1 - Focus of Expansion (pg 5)
7.2.2 - Adjacency, Depth, and Collision (pg 7)
7.2.3 - Surface Orientation and Edge Detection (pg 8)
7.2.4 - Egomotion (pg 12)

7.3 - Understanding Image Sequences (pg 1)

7.3.1 - Calculating Flow from Discrete Images (pg 1)
7.3.2 - Rigid Bodies from Motion (pg 4)
7.3.3 - Interpretation of Moving Light Displays - A Domain-Independent Approach (pg 8)
7.3.4 - Human Motion Understanding - A Model-Directed Approach (pg 11)
7.3.5 - Segmented Images (pg 14)

8 - Representation of Two-Dimensional Geometric Structures

8.1 - Two-Dimensional Geometric Structures (pg 4)

8.2 - Boundary Representations (pg 5)

8.2.1 - Polylines (pg 5)
8.2.2 - Chain Codes (pg 8)
8.2.3 - The Ψ-s Curve (pg 10)
8.2.4 - Fourier Descriptors (pg 11)
8.2.5 - Conic Sections (pg 12)
8.2.6 - B-Splines (pg 12)
8.2.7 - Strip Trees (pg 17)

8.3 - Region Representations (pg 1)

8.3.1 - Spatial Occupancy Array (pg 1)
8.3.2 - y Axis (pg 2)
8.3.3 - Quad Trees (pg 3)
8.3.4 - Medial Axis Transform (pg 6)
8.3.5 - Decomposing Complex Areas (pg 7)

8.4 - Simple Shape Properties (pg 8)

8.4.1 - Area (pg 8)
8.4.2 - Eccentricity (pg 9)
8.4.3 - Euler Number (pg 9)
8.4.4 - Compactness (pg 10)
8.4.5 - Slope Density Function (pg 10)
8.4.6 - Signatures (pg 11)
8.4.7 - Concavity Trees (pg 12)
8.4.8 - Shape Numbers (pg 12)

9 - Representations of Three-Dimensional Structures

9.1 - Solids and their Representation (pg 1)

9.2 - Surface Representations (pg 2)

9.2.1 - Surface with Faces (pg 2)
9.2.2 - Surfaces Based on Splines (pg 5)
9.2.3 - Surfaces That Are Functions on the Sphere (pg 7)

9.3 - Generalized Cylinder Representations (pg 1)

9.3.1 - Generalized Cylinder Coordinate Systems and Properties (pg 2)
9.3.2 - Extracting Generalized Cylinders (pg 5)
9.3.3 - A Discrete Volumetric Version of the Skeleton (pg 7)

9.4 - Volumetric Representations (pg 7)

9.4.1 - Spatial Occupancy (pg 7)
9.4.2 - Cell Decomposition (pg 8)
9.4.3 - Constructive Solid Geometry (pg 9)
9.4.4 - Algorithms for Solid Representations (pg 11)

9.5 - Understanding Line Drawings (pg 1)

9.5.1 - Matching Line Drawings to Three-Dimensional Primitives (pg 3)
9.5.2 - Grouping Regions Into Bodies (pg 4)
9.5.3 - Labeling Lines (pg 6)
9.5.4 - Reasoning About Planes (pg 11)

10 - Knowledge Representation and Use

10.1 - Representations (pg 4)

10.1.1 - The Knowledge Base - Models and Processes (pg 5)
10.1.2 - Analogical and Propositional Representations (pg 6)
10.1.3 - Procedural Knowledge (pg 8)
10.1.4 - Computer Implementations (pg 9)

10.2 - Semantic Nets (pg 1)

10.2.1 - Semantic Net Basics (pg 1)
10.2.2 - Semantic Nets for Inference (pg 5)

10.3 - Semantic Net Examples (pg 1)

10.3.1 - Frame Implementations (pg 1)
10.3.2 - Location Networks (pg 2)

10.4 - Control Issues in Complex Vision Systems (pg 1)

10.4.1 - Parallel and Serial Computation (pg 2)
10.4.2 - Hierarchical and Heterarchical Control (pg 2)
10.4.3 - Belief Maintenance and Goal Achievement (pg 7)

11 - Matching

11.1 - Aspects of Matching (pg 1)

11.1.1 - Interpretation: Construction, Matching, and Labeling (pg 1)
11.1.2 - Matching Iconic, Geometric, and Relational Structures (pg 2)

11.2 - Graph-Theoretical Algorithms (pg 4)

11.2.1 - The Algorithms (pg 6)
11.2.2 - Complexity (pg 8)

11.3 - Implementing Graph-Theoretical Algorithms (pg 1)

11.3.1 - Matching Metrics (pg 1)
11.3.2 - Backtrack Search (pg 4)
11.3.3 - Association Graph Techniques (pg 5)

11.4 - Matching in Practice (pg 1)

11.4.1 - Decision Trees (pg 2)
11.4.2 - Decision Tree and Subgraph Isomorphism (pg 7)
11.4.3 - Informal Feature Classification (pg 8)
11.4.4 - A Complex Matcher (pg 10)

12 - Inference

12.1 - First Order Predicate Calculus (pg 2)

12.1.1 - Clause-Form Syntax (Informal) (pg 2)
12.1.2 - Nonclausal Syntax and Logic Semantics (Informal) (pg 3)
12.1.3 - Converting Nonclausal Form to Clauses (pg 5)
12.1.4 - Theorem Proving (pg 6)
12.1.5 - Predicate Calculus and Semantic Networks (pg 8)
12.1.6 - Predicate Calculus and Knowledge Representation (pg 10)

12.2 - Computer Reasoning (pg 1)

12.3 - Production Systems (pg 2)

12.3.1 - Production System Details (pg 4)
12.3.2 - Pattern Matching (pg 5)
12.3.3 - An Example (pg 7)
12.3.4 - Production System Pros and Cons (pg 12)

12.4 - Scene Labeling and Constraint Relaxation (pg 1)

12.4.1 - Consistent and Optimal Labelings (pg 1)
12.4.2 - Discrete Labeling Algorithms (pg 3)
12.4.3 - A Linear Relaxation Operator and a Line-Labeling Example (pg 8)
12.4.4 - A Nonlinear Operator (pg 12)
12.4.5 - Relaxation as Linear Programming (pg 13)

12.5 - Active Knowledge (pg 1)

12.5.1 - Hypotheses (pg 2)
12.5.2 - HOW-TO and SO-WHAT Processes (pg 2)
12.5.3 - Control Primitives (pg 2)
12.5.4 - Aspects of Active Knowledge (pg 4)

13 - Goal Achievement

13.1 - Symbolic Planning (pg 2)

13.1.1 - Representing the World (pg 2)
13.1.2 - Representing Actions (pg 4)
13.1.3 - Stacking Blocks (pg 5)
13.1.4 - The Frame Problem (pg 7)

13.2 - Planning with Costs (pg 1)

13.2.1 - Planning, Scoring, and Their Interaction (pg 2)
13.2.2 - Scoring Simple Plans (pg 2)
13.2.3 - Scoring Enhanced Plans (pg 7)
13.2.4 - Practical Simplifications (pg 8)
13.2.5 - A Vision System Based on Planning (pg 9)

A1 - Some Mathematical Tools

A1.1 - Coordinate Systems (pg 1)

A1.1.1 - Cartesian (pg 1)
A1.1.2 - Polar and Polar Space (pg 1)
A1.1.3 - Spherical and Cylindrical (pg 2)
A1.1.4 - Homogeneous Coordinates (pg 3)

A1.2 - Trigonometry (pg 4)

A1.2.1 - Plane Trigonometry (pg 4)
A1.2.2 - Spherical Trigonometry (pg 5)

A1.3 - Vectors (pg 5)

A1.4 - Matrices (pg 7)

A1.5 - Lines (pg 10)

A1.5.1 - Two Points (pg 10)
A1.5.2 - Point and Direction (pg 10)
A1.5.3 - Slope and Intercept (pg 10)
A1.5.4 - Ratios (pg 10)
A1.5.5 - Normal and Distance from Origin (Line Equation) (pg 11)
A1.5.6 - Parametric (pg 12)

A1.6 - Planes (pg 12)

A1.7 - Geometric Transformations (pg 13)

A1.7.1 - Rotation (pg 13)
A1.7.2 - Scaling (pg 14)
A1.7.3 - Skewing (pg 15)
A1.7.4 - Translation (pg 15)
A1.7.5 - Perspective (pg 15)
A1.7.6 - Transforming Lines and Planes (pg 16)
A1.7.7 - Summary (pg 16)

A1.8 - Camera Calibration and Inverse Perspective (pg 1)

A1.8.1 - Camera Calibration (pg 2)
A1.8.2 - Inverse Perspective (pg 3)

A1.9 - Least-Squared-Error Fitting (pg 4)

A1.9.1 - Pseudo-Inverse Method (pg 5)
A1.9.2 - Principal Axis Method (pg 6)
A1.9.3 - Fitting Curves by the Pseudo-Inverse Method (pg 7)

A1.10 - Conics (pg 8)

A1.11 - Interpolation (pg 9)

A1.11.1 - One-Dimensional (pg 9)
A1.11.2 - Two-Dimensional (pg 10)

A1.12 - The Fast Fourier Transform (pg 10)

A1.13 - The Icosahedron (pg 12)

A1.14 - Root Finding (pg 13)

A2 - Advanced Control Mechanisms

A2.1 - Standard Control Structures (pg 1)

A2.1.1 - Recursion (pg 2)
A2.1.2 - Co-Routining (pg 2)

A2.2 - Inherently Sequential Mechanisms (pg 3)

A2.2.1 - Automatic Backtracking (pg 3)
A2.2.2 - Context Switching (pg 4)

A2.3 - Sequential or Parallel Mechanisms (pg 4)

A2.3.1 - Modules and Messages (pg 4)
A2.3.2 - Priority Job Queue (pg 6)
A2.3.3 - Pattern-Directed Invocation (pg 8)
A2.3.4 - Blackboard Systems (pg 9)

Color Supplement

Author Index (pg 1)

Subject Index (pg 5)

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