Falkena, R. (2006) Object Tracking in Presence of Occlusion Using a Layered Image Representation. Master's Thesis / Essay, Computing Science.
|
Text
Infor_Ma_2006_RFalkena.CV.pdf - Published Version Download (2MB) | Preview |
Abstract
Daily life scenes are often recorded on video, for future analysis or to be watched at real-time. What makes those scenes of interest to the people who record them, are the objects moving around in them. Information gained from tracks travelled by the objects can be used in numerous application fields, amongst which are video compression, analysis of animal behavior, and, in the real-time case, video surveillance and traffic monitoring. Tracking an object in a scene is an easy task for a human being. With the least of effort we follow the object around, even when its appearance or shape changes, or when it is temporarily out of sight. Amongst other problems, object occlusion is one of the hardest problems faced by an automated object tracking system. A lot of work is done on methods able to track objects through occlusions at real-time. This Master's Thesis concentrates on object tracking in presence of occlusion. A promising method from the class of trackers using a layered image representation was selected and implemented, to be compared to a fast multi-rolution graph-based method developed at the University of Salerno. Comparison is done using a specially developed database of artificial test sets, which tests both trackers on specific basic and advanced events possibly occurring in daily life scenes. A well-known real-world test set is also used. Based on the outcome of the tests, suggestions are done for further research in the field of real-time trackers with occlusion handling.
Item Type: | Thesis (Master's Thesis / Essay) |
---|---|
Degree programme: | Computing Science |
Thesis type: | Master's Thesis / Essay |
Language: | English |
Date Deposited: | 15 Feb 2018 07:30 |
Last Modified: | 15 Feb 2018 07:30 |
URI: | https://fse.studenttheses.ub.rug.nl/id/eprint/8905 |
Actions (login required)
View Item |