CS 131 Computer Vision: Foundations and Applications Fall 2014-2015
Event Type | Date | Description | Course Materials |
Lecture 1 | Tuesday September 26 | Course introduction Computer vision overview Course logistics | Introduction slides [pptx] [pdf] Lecture 1 notes [pdf] |
Lecture 2 | Thursday September 28 | Color + Math basics Physics of light Human encoding of color Color Spaces White Balancing Vectors and Matrices | Color spaces slides [pptx] [pdf] Lecture 2 notes [pdf] python/numpy tutorial [pdf] |
HW0 Due | Monday October 2, 11:59pm | Homework #0 due Basics | |
Lecture 3 | Tuesday October 3 | Linear algrebra Transformation matrixes Eigenvalues and eigenvectors Matrix calculus and hessian | Linear algebra slides [pptx] [pdf] Lecture 3 notes [pdf] |
Lecture 4 | Thursday October 5 | Pixels and filters Pixels and image representation Linear systems Convolutions and cross-correlations | Pixels and filters slides [pptx] [pdf] Lecture 4 notes [pdf] |
HW1 Due | Monday October 10, 11:59pm | Homework #1 due Filters - Instagram | |
Lecture 5 | Tuesday October 10 | Edge detection Derivative of gaussians Sobel filters Canny edge detector | Edge detection slides [pptx] [pdf] Lecture 5 notes [pdf] |
Lecture 6 | Thursday October 12 | Features and fitting RANSAC Local features Harris corner detection | Features and fitting slides [pptx] [pdf] Lecture 6 notes [pdf] |
Lecture 7 | Tuesday October 17 | Feature descriptors Difference of gaussians Scale invariant feature transform Image stitching | Feature descriptors slides [pptx] [pdf] Lecture 7 notes [pdf] |
HW2 Due | Wednesday October 18, 11:59pm | Homework #2 due Edges - Smart car lane detection | |
Lecture 8 | Thursday October 19 | Resizing Energy function Seam carving | Lecture 8 notes [pdf] |
Lecture 9 | Tuesday October 24 | Semantic segmentation Gestalt theory of perceptual grouping Aggomerative clustering Superpixels and oversegmentation | Semantic segmentation slides [pptx] [pdf] Lecture 9 notes [pdf] |
HW3 Due | Wednesday October 25, 11:59pm | Homework #3 due Panorama - Image stitching | |
Lecture 10 | Thursday October 26 | Clustering K-means Mean shift | Clustering slides [pptx] [pdf] Lecture 10 notes [pdf] |
Lecture 11 | Tuesday October 31 | Object recognition Nearest neighbors Classification pipeline | Object recognition slides [pptx] [pdf] Lecture 11 notes [pdf] |
HW4 Due | Wednesday November 1, 11:59pm | Homework #4 due Resizing - Seam carving | |
Lecture 12 | Thursday November 2 | Dimensionality reduction Singular value decomposition Principal component analysis | Dimensionality reduction slides [pptx] [pdf] Lecture 12 notes [pdf] |
Lecture 13 | Tuesday November 7 | Face identification Eigenfaces and fisherfaces Linear Discriminant Analysis | Face identification slides [pptx] [pdf] Lecture 13 notes [pdf] |
HW5 Due | Wednesday November 8, 11:59pm | Homework #5 due Segmentation - Clustering | |
Lecture 14 | Thursday November 9 | Visual Bag of Words Texture features Visual bag of words Image pyramids | Visual bag of words slides [pptx] [pdf] Lecture 14 notes [pdf] |
Lecture 15 | Tuesday November 14 | Detecting objects by parts Deformable parts model Object detection | Deformable parts slides [pptx] [pdf] Lecture 15 notes [pdf] |
HW6 Due | Wednesday November 15, 11:59pm | Homework #6 due Recognition - Classification | |
Lecture 16 | Thursday November 16 | Image classification Imagenet Semantic hierarchy Fine grained classes | Lecture 16 notes [pdf] |
Lecture 17 | Tuesday November 28 | Motion Optical Flow Lucas-Kanade method Horn-Schunk Method Pyramids for large motion Common Fate | Lecture 17 notes [pdf] |
HW7 Due | Wednesday November 29, 11:59pm | Homework #7 due Object detection - constellation models | |
Lecture 18 | Thursday November 30 | Tracking Feature Tracking Lucas Kanade Tomasi (KLT) tracker | Lecture 18 notes [pdf] |
Lecture 19 | Tuesday December 5 | Introduction to deep learning Convolutional neural networks Backpropagation | Deep learning slides [pptx] [pdf] Lecture 19 notes [pdf] |
HW8 Due | Wednesday December 6, 11:59pm | Homework #8 due Tracking - Optical flow | |
Lecture 20 | Thursday December 7 | Final Review Summary of class | |
Final | Monday | December 11,12:15 to 3:15pm Location: 320-105 | Practice final [pdf] |