1. KRISTIN LAM REU WEEKS 1 & 2

2. MATERIAL COVERED MATLAB basics Edge Detection Harris Corner Detector Adaboost Face Detection Optical Flow Lucas-Kanade Method Bag of Features

3. 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

4. CANNY

5. SOBEL

6. LAPLACIAN OF GAUSSIAN

7. EDGE DETECTION ASSIGNMENT

8. FINDING THE GRADIENT Calculate the gradient of the image.

9. THRESHOLDING Pick a threshold and binarize it to get edges that describe the image well.

10. PYRAMIDS Create a pyramid of the image with 3 levels.

11. 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.

12. HARRIS CORNER DETECTOR

13. ADABOOST FACE DETECTION

14. 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

15. OPTICAL FLOW

16. LUCAS-KANADE

17. BAG OF FEATURES Technique for the visual classification of objects and categories of objects/textures

18. 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