As the use of video becomes increasingly popular and wide spread in the areas of broadcast services, internet, entertainment and security-related applications, providing means for fast. automated, and effective techniques to represent video based on its content, such as objects and meanings, is important topic of research. In many applications.. removing the hand shaking effect and making video images stable and clear or decomposing (and then transmitting) the video content into a collection of meaningful objects is a necessity. Therefore automatic techniques for video stabilization, extraction of objects from video data as well as transmitting their shapes, motion and texture at very low bit rates over error networks, are desired. In this thesis the design of a new low bit rate codec is presented. Furthermore a method about video stabilization is introduced. The main technical contributions resulted from this work are as follows. Firstly, an adaptive change detection algorithm identifies the objects from the background. The luminance difference between framer~ in the first stage, is modelled so as to separate contributions caused by noise and illumination variations from those caused by meaningful moving objects. In the second stage the segmentation tool based on image blocks, histograms and clustering algorithms segments the difference image into areas corresponding to objects. In the third stage morphological edge detection, contour analysis, and object labelling are the main tasks of the proposed segmentation algorithm. Secondly, a new low bit rate codec is designed and analyzed based on the proposed segmentation tool. The estimated motion vectors inside the change detection mask, the comer points of the shapes as well as the residual information inside the motion failure regions are transmitted to the decoder using different coding techniques, thus achieving efficient compression. Thirdly, a novel approach of estimating and removing unwanted video motion, which does not require accelerators or gyros, is presented. The algorithm estimates the camera motion from the incoming video stream and compensates for unwanted translation and rotation. A synchronization unit supervises and generates the stabilized video sequence. The reliability of all the proposed algorithms is demonstrated by extensive experimentation on various video shots.
Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:517469 |
Date | January 2009 |
Creators | Tsoligkas, Nick A. |
Publisher | Teesside University |
Source Sets | Ethos UK |
Detected Language | English |
Type | Electronic Thesis or Dissertation |
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