This thesis analyses videos in two distinct ways so as to improve both human understanding
and the computer description of events that unfold in video sequences.
Qualitative analysis can be used to understand a scene in which many details are not
needed. However, for there to be an accurate interpretation of a scene, a computer
system has to first evaluate discretely the events in a scene. Such a method must
involve structural features and the shapes of the objects in the scene.
In this thesis we perform qualitative analysis on a road scene and generate terms
that can be understood by humans and that describe the status of the traffic and its
congestion. Areas in the video that contain vehicles are identified regardless of scale.
The movement of the vehicles is further identified and a rule-based technique is used
to accurately determine the status of the traffic and its congestion.
Occlusion is a common problem in scene analysis tracking. A novel technique is developed
to vertically separate groups of people in video sequences. A histogram is
generated based on the shape of a group of people and its valleys are identified. A
vertical seam for each valley is then detected using the intensity of the edges. This is
then used as the separation boundary between the different individuals. This could
definitely improve the tracking of people in a crowd.
Both techniques achieve good results, with the qualitative analysis accurately describing
the status and congestion of a traffic scene, while the structural analysis can
separate a group of people into distinctly separate persons. / Thesis (M.Sc.)-University of KwaZulu-Natal, Westville, 2011.
| Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:ukzn/oai:http://researchspace.ukzn.ac.za:10413/9740 |
| Date | 17 October 2013 |
| Creators | Brits, Alessio. |
| Contributors | Tapamo, Jules-Raymond. |
| Source Sets | South African National ETD Portal |
| Language | en_ZA |
| Detected Language | English |
| Type | Thesis |
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