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IROS
2008
IEEE

Frame rate object extraction from video sequences with self organizing networks and statistical background detection

10 years 3 hour ago
Frame rate object extraction from video sequences with self organizing networks and statistical background detection
— In many computer vision related applications it is necessary to distinguish between the background of an image and the objects that are contained in it. This is a difficult problem because of the double constraint on the available time and the computational cost of robust object extraction algorithms. This paper builds upon former work on combining the strong theoretical foundations of clustering with the speed of other approaches. It is based on a novel Self Organizing Network (SON) which has a robust initialization schema and is able to find the number of objects in an image or grid. The main contribution of our extension is that it eliminates the use of a threshold, allowing the algorithm to work on continuous, while having a complexity that remains linear with respect to the number of pixels or cells.
Thiago C. Bellardi, Dizan Vasquez, Christian Laugi
Added 31 May 2010
Updated 31 May 2010
Type Conference
Year 2008
Where IROS
Authors Thiago C. Bellardi, Dizan Vasquez, Christian Laugier
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