KRISTIN LAM REU WEEKS 1 & 2. MATERIAL COVERED MATLAB basics Edge Detection Harris Corner...

K R I S T I N L A M

REU WEEKS 1 & 2

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