Automatic detection of salient objects for a video database system
Author
Sevilmiş, Tarkan
Advisor
Güdükbay, Uğur
Date
2005Publisher
Bilkent University
Language
English
Type
ThesisItem Usage Stats
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Abstract
Recently, the increase in the amount of multimedia data has unleashed the development
of storage techniques. Multimedia databases is one of the most popular
of these techniques because of its scalability and ability to be queried by the
media features. One downside of these databases is the necessity for processing
of the media for feature extraction prior to storage and querying. Ever growing
pile of media makes this processing harder to be completed manually. This is the
case with BilVideo Video Database System, as well. Improvements on computer
vision techniques for object detection and tracking have made automation of this
tedious manual task possible. In this thesis, we propose a tool for the automatic
detection of objects of interest and deriving spatio-temporal relations between
them in video frames. The proposed framework covers the scalable architecture
for video processing and the stages for cut detection, object detection and tracking.
We use color histograms for cut detection. Based on detected shots, the
system detects salient objects in the scene, by making use of color regions and
camera focus estimation. Then, the detected objects are tracked based on their
location, shape and estimated speed.