reu report i
DESCRIPTION
REU Report I. Alla Petrakova UCF. Material covered. MATLAB Derivatives, Filters, Thresholding , Equalization, etc. Correlation, Convolution Edge Detection ( Sobel , Laplacian of Gaussian, Canny) Harris Corner Detector SIFT Adaboost , face detection SVM Optical Flow Bag of Features. - PowerPoint PPT PresentationTRANSCRIPT
REU REPORT IAlla PetrakovaUCF
MATERIAL COVERED
MATLAB Derivatives, Filters, Thresholding, Equalization, etc. Correlation, Convolution Edge Detection (Sobel, Laplacian of Gaussian, Canny) Harris Corner Detector SIFT Adaboost, face detection SVM Optical Flow Bag of Features
EDGE DETECTION - SOBEL
GAUSSIAN
EDGE DETECTION - SOBEL
LAPLACIAN OF GAUSSIAN
CANNY
HARRIS CORNER DETECTOR
HARRIS CORNER DETECTOR
SIFT – DENSE SAMPLING
SIFT – DESCRIPTORS INCLUDED
OPTICAL FLOWCOMPARING OUTPUTS – CE LIU
OPTICAL FLOW
Window size = 70
Window size = 40
SVM & BAG OF WORDS
SVM One of the biggest challenges Tried with sift, dense sift, scaled data Stubbornly stuck on 53% accuracy
Bag Of Words 47% to 53% accuracy
Possible solution: “A Practical Guide to Support Vector Classification Chih-Wei Hsu, Chih-
Chung Chang, and Chih-Jen Lin “ http://www.csie.ntu.edu.tw/~cjlin/papers/guide/guide.pdf
RESEARCH PROJECTS
“Trajectory Clustering: A Motion Pattern approach” by Mahdi M. Kalayeh Pattern recognition Analysing effects of applying various similarity measures Probabilistic Predictive Modelling
“Clustering in High Dimensional Data” by Gonzalo Vaca-Castano
“Cell Tracking and Lineage Construction” with Sarfaraz Hussein