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REU WEEKS 1 & 2 KRISTIN LAM MATERIAL COVERED • MATLAB basics • Edge Detection • Harris Corner Detector • Adaboost Face Detection • Optical Flow • Lucas-Kanade Method • Bag of Features EDGE DETECTION • Finds the boundaries of objects • Edges are defined by the discontinuity of intensities in the image • Common Edge Detectors • Canny • Sobel • Laplacian of Gaussian CANNY SOBEL LAPLACIAN OF GAUSSIAN EDGE DETECTION ASSIGNMENT FINDING THE GRADIENT Calculate the gradient of the image. THRESHOLDING Pick a threshold and binarize it to get edges that describe the image well. PYRAMIDS Create a pyramid of the image with 3 levels. HARRIS CORNER DETECTOR • In addition to edges, corners are used to find matching points between different frames. • The corner represents the point where two edges change. • The gradient of the image in both directions will have a high variation, which can be detected. HARRIS CORNER DETECTOR ADABOOST FACE DETECTION OPTICAL FLOW • Pattern of apparent motion of objects, surfaces, and edges caused by the relative motion between the observer and the scene • Can be used to measure velocities of objects • Lucas-Kanade method • Assumes displacement of the object between two frames is small • Uses “Least Squares,” a statistical method that limits the distance between a function and the data points of that function OPTICAL FLOW LUCAS-KANADE BAG OF FEATURES • Technique for the visual classification of objects and categories of objects/textures POTENTIAL PROJECTS • Multi-Target Tracking with Social Behavior Model by Yicong Tian • Multimodal Data Analysis for the Detection of Attention Deficit Hyperactive Disorder by Soumyabrata Dey
