@mastersthesis {xTort13, title = {Video Clustering Using Camera Motion}, year = {2013}, abstract = {

This document contains the work done in INP Grenoble during the second semester of the academic year 2011-2012, completed in Barcelona during the firsts months of the 2012-2013. The work presented consists in a camera motion study in different types of video in order to group fragments that have some similarity in the content.\ 

In the document it is explained how the data extracted by the program Motion 2D, proportionated by the French university, are treated in order to represented them in a more simplified using motion histograms. It is also explained how the different distances between histograms are calculated and how its similarity is computed.\ 

Three different distances are used: Manhattan, Euclidean and Bhattacharyya, although in the project there can be found the explanation of some others a little bit more complicated. Different histogram configurations are used, using more or less bins to represent the motion.\ 

Every possible combination of the number of bins and distances are evaluated using a group of 30 fragments of video and the clustering algorithm K-Means. The clustering results are evaluated using F1-Score, a very popular measurement suitable for clustering algorithms and also classification.

}, url = {http://hdl.handle.net/2099.1/17337}, author = {Tort, Laura}, editor = {Xavier Gir{\'o}-i-Nieto and Rombaut, Mich{\`e}le and Pellerin, Denis} }