Extracting Proper Features for Human Detection in Still Images, M.Sc. Thesis Sharif University of Technology ; Jamzad, Mansour (Supervisor)
Abstract
Human detection in still images is one of the hardest problems in object detection area. There are several challenges like articulation, pose variation, variant clothing, none uniform illumination, cluttered background and occlusion which make this problem more sophisticated than any other object detection problem. The general solution for this kind of problems is based on supervised learning that contains two main parts: 1-extracting proper features, 2- using proper classifier. The main focus of this thesis is on the first part, extracting proper features, which should be robust to mentioned challenges. Based on the level of extraction we can divide the features to four groups: 1-low-level,...
Cataloging briefExtracting Proper Features for Human Detection in Still Images, M.Sc. Thesis Sharif University of Technology ; Jamzad, Mansour (Supervisor)
Abstract
Human detection in still images is one of the hardest problems in object detection area. There are several challenges like articulation, pose variation, variant clothing, none uniform illumination, cluttered background and occlusion which make this problem more sophisticated than any other object detection problem. The general solution for this kind of problems is based on supervised learning that contains two main parts: 1-extracting proper features, 2- using proper classifier. The main focus of this thesis is on the first part, extracting proper features, which should be robust to mentioned challenges. Based on the level of extraction we can divide the features to four groups: 1-low-level,...
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