Phd Thesis: Tools for image analysis, representation, and compression

A real-time moving object extraction and tracing algorithm is proposed for videophone application. Semantic objects, mainly moving objects in this specified case, are extracted by block based change detection from first several frames. Improved active contour model is then utilized for object tracing. Since there is little difference between continuous two frames, only limited pixels need to be searched instead of whole frame scan so that computing complexity is greatly decreased. Therefore, it is able to be used for real-time applications such as that in videophone. However, previous active contour model is sensitive to noise. Error originating from noise traps accumulates and deteriorates the tracing results. So gradient projection (GP) and jump back (JB) mechanisms are introduced to suppress noise trap effect and error accumulation in this paper. Experiment results demonstrate that proposed algorithm is an efficient noise tolerable real-time approach.

Real-time automatic moving object extraction and tracing based on improved active contour model

A real-time movingobject extraction andtracing algorithm isproposed forvideophone application. Semantic objects, mainly moving objects inthis specified case, areextracted byblock based change detection from first several frames. Improved active contour modelis thenutilized forobject tracing. Sincethereislittle difference between continuous twoframes, onlylimited pixels needtobesearched instead ofwholeframe scanso that computing complexity isgreatly decreased. Therefore, itisable tobeusedforreal-time applications suchasthat invideophone. However, previous active contour modelis sensitive tonoise. Errororiginating fromnoisetraps accumulates anddeteriorates thetracing results. So gradient projection (GP)andjumpback(JB)mechanisms areintroduced tosuppress noise trapeffect anderror accumulation in thispaper.Experiment results demonstrate that proposed algorithm isanefficient noise tolerable real-time approach.

http://ieeexplore.ieee.org/iel5/10632/33566/01595368.pdf

Real-timeautomatic moving objectextraction and tracingbasedon improved activecontour model

A semi-automatic algorithm to extract the semantic video object from image sequences is proposed. Different schemes are used to get the initial video object in the first frame and other frames of a sequence. In the first frame, two polygons are input by the user to specify the area in which the object boundary is located. Then the video object is extracted automatically based on only the first frame. In the following frames, the image frame is segmented into intensity homogeneous regions. The moving regions are detected by a morphological filter, non-moving regions are selected by the object model obtained from the previous frame. These regions form the initial video object. In each frame, after the initial object is available, the edges which belong to the video object of interest are selected by a local object contour model. Finally, an active contour model (snake) is applied to extract the final object contour.

Z. Lu

Papers

Semi-automatic semantic object extraction for video coding