- Tracking Objects with Covariance and Mean-Shift
Covariance-based object matching with generalized eigenvalues, and mean-shift tracking with Epanechnikov-weighted color histograms.
7 min - Motion History Images and Optical Flow
Image differencing with morphological cleanup, MEI and MHI temporal representations, similitude moments on motion images, and Lucas-Kanade optical flow.
8 min - Shape Moments and PCA on a Box of Dots
Computing image moments from scratch, eigenanalysis of 2D data, confidence ellipses, decorrelation, and dimensionality reduction.
6 min - Image Pyramids and Background Subtraction
Gaussian and Laplacian pyramids from scratch, single vs multi-frame background subtraction, and connected components.
8 min - Finding Edges with Gaussians, Sobel, and Canny
Gaussian smoothing, implementing derivative filters from scratch, Sobel vs Canny, and making Keanu Reeves look like A Scanner Darkly.
7 min - Reading Images and the NTSC Grayscale Formula
Loading images, the NTSC grayscale formula, and a checkerboard. First computer vision homework done in Python instead of MATLAB.
4 min - Multithreaded Restaurant Simulation in C++14
Building a concurrent restaurant simulation with mutexes, condition variables, and semaphores to coordinate diners, cooks, and shared machines.
23 min - Fractals for Image Classification Feature Extraction
Exploring how fractal geometry, specifically Hilbert curves, can provide a novel approach to feature extraction in image classification.
11 min
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