Applied Computer Vision Lecture Schedule - Revision history

Dvernon at 17:52, 22 August 2017

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Dvernon at 23:47, 20 August 2017

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Dvernon at 23:11, 20 August 2017

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Dvernon at 21:11, 20 August 2017

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Dvernon at 21:10, 20 August 2017

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Dvernon at 21:10, 20 August 2017

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Dvernon at 21:07, 20 August 2017

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Dvernon at 19:38, 20 August 2017

2017-08-20T19:38:46Z

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@@ Line 29: / Line 29: @@
 | 3
 | Optics, sensors, and image formation
+| Illumination, projections, lenses, Gauss lens equation, field of view, depth of field, CMOS and CCD sensors, colour sensors, noise, resolution.
+|
+|
@@ Line 36: / Line 36: @@
 | 4
 | Image acquisition and image representation
+| Sampling and quantization, Shannon's sampling theorem, Nyquist frequency, Nyquist sampling rate, aliasing, resolution, space-variant sampling, log-polar images, dynamic range, colour spaces: HIS, HLS, HSV
+|
+|

@@ Line 84: / Line 84: @@
 | Mon. 2 Oct.
 | 11
+| Image features
+| Harris and Difference of Gaussian interest point operators
+|
+|
@@ Line 91: / Line 91: @@
 | Wed. 4 Oct.
 | 12
+|  Image features
+|  SIFT feature descriptor
+|
+|
@@ Line 98: / Line 98: @@
 | Mon. 9 Oct.
 | 13
+| Object recognition
+| Template matching; normalized cross-correlation; chamfer matching
+|
+|
@@ Line 105: / Line 105: @@
 | Wed. 11 Oct.
 | 14
+| Object recognition
+| 2D shape features; statistical pattern recognition
+|
+|
@@ Line 112: / Line 112: @@
 | Mon. 16 Oct.
 | 15
+|  Object recognition
+| Hough transform for parametric curves: lines, circles, and ellipses
+|
+|
@@ Line 119: / Line 119: @@
 | Wed. 18 Oct.
 | 16
+|  Object recognition
+| Generalized Hough transform; extension to codeword features
+|
+|
@@ Line 126: / Line 126: @@
 | Mon. 23 Oct.
 | 17
+| Object recognition
+| Colour histogram matching and back-projection
+|
+|
@@ Line 133: / Line 133: @@
 | Wed. 25 Oct.
 | 18
+| Object recognition
+| Haar features and boosted classifiers
+|
+|
@@ Line 140: / Line 140: @@
 | Mon. 30 Oct.
 | 19
+|  Object recognition
+|  Histogram of Oriented Gradients (HOG) feature descriptor
+|
+|
@@ Line 147: / Line 147: @@
 | Wed. 1 Nov.
 | 20
+|  Video image processing
+|  Background subtraction and object tracking
+|
+|
@@ Line 154: / Line 154: @@
 | Mon. 6 Nov.
 | 21
+|  3D vision
+| Homogeneous transformations. Perspective transformation. Camera model and inverse perspective transformation
+|
+|
@@ Line 161: / Line 161: @@
 | Wed. 8 Nov.
 | 22
+| Stereo vision.
+| Stereo correspondence, Epipolar geometry
+|
+|
@@ Line 168: / Line 168: @@
 | Mon. 13 Nov.
 | 23
+|  Optical flow
+|
+|
@@ Line 175: / Line 175: @@
 | Wed. 15 Nov.
 | 24
+|  Visual attention
+|  Saliency, Bottom-up and top-down attention
+|
+|
@@ Line 182: / Line 182: @@
 | Mon. 20 Nov.
 | 25
+|  Clustering, grouping, and segmentation
+| Gestalt principles. Clustering algorithms
+|
+|
@@ Line 189: / Line 189: @@
 | Wed. 22 Nov.
 | 26
+|  Object recognition in 3D
+| Object detection, object recognition, object categorisation
+|
+|
@@ Line 196: / Line 196: @@
 | Mon. 27 Nov.
 | 27
+|  Affordances
+|
+|
@@ Line 203: / Line 203: @@
 | Wed. 29 Nov.
 | 28
+| Computer vision and machine learning
+|
+|
@@ Line 210: / Line 210: @@
 | Mon. 4 Dec.
 | 29
+|  Computer vision and machine learning
+|
+|
@@ Line 217: / Line 217: @@
 | Wed. 6 Dec.
 | 30
+|  Computer vision and machine learning
+|
+|

@@ Line 85: / Line 85: @@
 | 11
+|
-|  Queue (FIFO ADT). Implementation using List ADT (array and linked-list).   Comparison of order of complexity.  Dedicated ADT. Circular queues.  Queue applications.
-|  [http://www.vernon.eu/04-630/04-630_Lecture_11_Queues.pdf Lecture 11 Slides]. [http://www.vernon.eu/04-630/poisson.pdf  On the Simulation of Random Events].
+|
 |- style="vertical-align: top;"

@@ Line 16: / Line 16: @@
 | Overview
 | Human and computer vision
-|[http://www.vernon.eu/ACV/ACV_01.pdf Lecture 1 Slides]. Szeliski 2010, Sections 1.1 and 1.2. Kragic and Vincze, 2010.   [http://www.cs.ubc.ca/~lowe/vision.html David Lowe's website of industrial vision systems].
+|[http://www.vernon.eu/ACV/ACV_01.pdf Lecture 1 Slides]. Szeliski 2010, Sections 1.1 and 1.2. Kragic and Vincze, 2010.   <!-- [http://www.cs.ubc.ca/~lowe/vision.html David Lowe's website of industrial vision systems]. -->
+|
 |- style="vertical-align: top;"

@@ Line 5: / Line 5: @@
 <small>
 {| class="wikitable"
-! scope="col" style="width: 7%;" | Date
+! scope="col" style="width: 7%;" | Date                           <!-- 7% -->
-! scope="col" style="width: 3%;" | Lecture
+! scope="col" style="width: 3%;" | Lecture                      <!-- 3% -->
-! scope="col" style="width: 14%;" | Topic
+! scope="col" style="width: 20%;" | Topic                         <!-- 14% -->
-! scope="col" style="width: 50%;" | Material covered
+! scope="col" style="width: 30%;" | Material covered     <!-- 50% -->
-! scope="col" style="width: 13%;" | Reading
+! scope="col" style="width: 20%;" | Reading                    <!-- 13% -->
-! scope="col" style="width: 13%;" | Assignments
+! scope="col" style="width: 20%;" | Assignments            <!-- 13% -->
 |- style="vertical-align: top;"
 | Mon. 28 Aug.

@@ Line 14: / Line 14: @@
 | Mon. 28 Aug.
 | 1
-| Overview of human and computer vision
+| Overview
+| Human and computer vision
 |[http://www.vernon.eu/ACV/ACV_01.pdf Lecture 1 Slides]. Szeliski 2010, Sections 1.1 and 1.2. Kragic and Vincze, 2010.   [http://www.cs.ubc.ca/~lowe/vision.html David Lowe's website of industrial vision systems].
+|
@@ Line 21: / Line 21: @@
 | Wed. 30 Aug.
 | 2
-| OpenCV and software development tools for course work
+| Software tools
+|  OpenCV, Software development tools for course work
 | [http://www.vernon.eu/ACV/ACV_02.pdf Lecture 2 Slides].
+|
@@ Line 43: / Line 43: @@
 | 5
 | Image processing
-| point & neighbourhood operations, image filtering, convolution, Fourier transform
+| Point & neighbourhood operations, image filtering, convolution, Fourier transform
+|
+|

@@ Line 16: / Line 16: @@
 | Overview of human and computer vision
+|
-|[http://www.vernon.eu/ACV/ACV_01.pdf Lecture 1 Slides]. Szeliski 2010, Chapter 1. ]
+|[http://www.vernon.eu/ACV/ACV_01.pdf Lecture 1 Slides]. Szeliski 2010, Sections 1.1 and 1.2. Kragic and Vincze, 2010.   [http://www.cs.ubc.ca/~lowe/vision.html David Lowe's website of industrial vision systems].
+|
 |- style="vertical-align: top;"
 | Wed. 30 Aug.
 | 2
-| Formalisms for Representing Algorithms
+| OpenCV and software development tools for course work
-| Definition of an algorithm. Modelling software. Relational modelling. State modelling. Practical representations. Pseudo code. Flow charts. Finite state machines. UML. Predicate logic. Analysis.
-| [http://www.vernon.eu/04-630/04-630_Lecture_02_Formalisms_for_Representing_Algorithms.pdf Lecture 2 Slides]. Harel 2004, Chapters 1 and 2.
+| [http://www.vernon.eu/ACV/ACV_02.pdf Lecture 2 Slides].
-| [http://www.vernon.eu/04-630/04-630_Assignment_1.pdf Assignment 1]
 |- style="vertical-align: top;"
 | Mon. 4 Sept.
 | 3
-| Analysis of Complexity I
+| Optics, sensors, and image formation
-| Performance of algorithms, time and space tradeoff, worst case and average case performance. Big O notation. Recurrence relationships. Analysis of complexity of iterative and recursive algorithms. Recursive vs. iterative algorithms: runtime memory implications.
-| [http://www.vernon.eu/04-630/04-630_Lecture_03_Analysis_of_Complexity_I.pdf Lecture 3 Slides]. Aho et al. 1983, Chapter 1.
+|
 |- style="vertical-align: top;"
 | Wed. 6 Sept.
 | 4
-| Analysis of Complexity II
+| Image acquisition and image representation
-|  Complexity theory: tractable vs intractable algorithmic complexity. Example intractable problems: travelling salesman problem, Hamiltonian circuit, 3-colour problem, SAT, cliques. Determinism and non-determinism. P, NP, and NP-Complete classes of algorithm.
-| [http://www.vernon.eu/04-630/04-630_Lecture_04_Analysis_of_Complexity_II.pdf Lecture 4 Slides]. Aho et al. 1983, Chapter 1.
-|  [http://www.vernon.eu/04-630/04-630_Assignment_2.pdf Assignment 2]
 |- style="vertical-align: top;"
 | Mon. 11 Sept.
 | 5
-| Searching and Sorting Algorithms I
+| Image processing
-| Linear and binary search (iterative and recursive). In-place sorts: bubblesort (efficient and inefficient), selection sort, insertion sort.
+| point & neighbourhood operations, image filtering, convolution, Fourier transform
-| [http://www.vernon.eu/04-630/04-630_Lecture_05_Searching_and_Sorting_Algorithms_I.pdf Lecture 5 Slides]. Aho et al. 1983, Chapter 8.
+|
 |- style="vertical-align: top;"
 | Wed. 13 Sept.
 | 6
-| Searching and Sorting Algorithms I
+| Image processing
-| Not-in-place sorts: Quicksort, merge sort. Complexity analysis. Characteristics of a good sort. Speed, consistency, keys, memory usage, length & code complexity, stability. Other sorts ordered by complexity.
+| Morphological operations
-|[http://www.vernon.eu/04-630/04-630_Lecture_06_Searching_and_Sorting_Algorithms_II.pdf Lecture 6 Slides]. Aho et al. 1983, Chapter 8.
+|
 |- style="vertical-align: top;"
 | Mon. 18 Sept.
 | 7
-| Abstract Data Types (ADT)
+| Image processing
-| <!-- Vector example exercise. History of abstraction. --> Abstract Data Types (ADT). Information hiding. Types and typing. <!-- Encapsulation. Efficiency. --> Design Goals. Design practices.
+| Geometric operations
-| [http://www.vernon.eu/04-630/04-630_Lecture_07_Abstract_Data_Types.pdf Lecture 7 Slides].
+|
 |- style="vertical-align: top;"
 | Wed. 20 Sept.
 | 8
-| Containers, Dictionaries, and Lists I
+|Segmentation
-| Container and dictionaries: mechanisms for accessing data in a list.  List ADT.  Implementation with arrays.
+|Region-based approaches, binary thresholding, connected component analysis
-|  [http://www.vernon.eu/04-630/04-630_Lecture_08_Containers,_Dictionaries,_and_Lists_I.pdf Lecture 8 Slides].
-|  [http://www.vernon.eu/04-630/04-630_Assignment_3.pdf Assignment 3] <!-- <BR> [[Assignment 3 Status]] -->
 |- style="vertical-align: top;"
 | Mon. 25 Sept.
 | 9
-| Containers, Dictionaries, and Lists II
+| Segmentation
-| List ADT.  Implementation with linked lists. Doubly linked lists and circular lists. Performance considerations.
+| Edge detection
-|   [http://www.vernon.eu/04-630/04-630_Lecture_09_Containers,_Dictionaries,_and_Lists_II.pdf Lecture 9 Slides].
+|
 |- style="vertical-align: top;"
 | Wed. 27 Feb.
 | 10
-| Stacks
+| Segmentation
-| Stack (LIFO) ADT. Implementation using List ADT (array and linked-list). Comparison of order of complexity.  Stack applications, including token matching, evaluation of postfix expressions, and conversion of infix expressions to postfix.
+| Colour-based approaches; k-means clustering
-| [http://www.vernon.eu/04-630/04-630_Lecture_10_Stacks.pdf Lecture 10 Slides].
+|
 |- style="vertical-align: top;"
@@ Line 92: / Line 92: @@
 | 12
+|
-| Concepts and terminology: level, height, external and internal nodes, skinny, fat, complete, left-complete, perfect, multi-way, d-ary. Types of tree: binary, binary search, B-tree, 2-3 tree, AVL, Red-Black
-|  [http://www.vernon.eu/04-630/04-630_Lecture_12_Trees_I.pdf Lecture 12 Slides].
+|
 |- style="vertical-align: top;"
@@ Line 100: / Line 100: @@
+|
+|
-|  [http://www.vernon.eu/04-630/04-630_Lecture_13_Trees_II.pdf Lecture 13 Slides].
-| [http://www.vernon.eu/04-630/04-630_Lab_Exercise_1.pdf Lab Exercise 1]
 |- style="vertical-align: top;"
 | Wed. 11 Oct.