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Implementation and Evaluation of Content-aware Video Retargeting Techniques (Computer/Electrical Project)

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ABSTRACT

The purpose of this master thesis was to study different content-aware video retargeting techniques, concentrating on a generalization of seam carving for video. Focus have also been put on the possibility to combine different techniques to achieve better retargeting of both multi-shot video and single-shot video. This also involved significant studies of automatic cut detection and different measures of video content.

The work resulted in a prototype application for semi-automatic video retargeting, developed in Matlab. Three different retargeting techniques, seam carving, automated pan & scan and subsampling using bi-cubic interpolation, have been implemented in the prototype. The techniques have been evaluated and compared to each other from a content preservation perspective and a perceived quality perspective.

CUT DETECTION

A histogram of an image is found by counting the number of occurrences of each color in the image. The N-bin histogram is found by putting occurrences of colors in the bin which closest represents their value. The count of each bin is plotted. In the case of an image I with 9 pixels with 3 different colors taking values from the set { 1 , 2 , 3 }, the 3-bin histogram h 3 ( I ) may look like in Figure 2.1. In Figure 2.1 five pixels have the value 1, two pixels have the value 2 and two pixels have the value 3

 

 

 

 
Source: Linköping University
Author: Holmer, Stefan

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