Foreground Segmentation of Moving Objects
Independent thesis Advanced level (professional degree), 20 credits / 30 HE creditsStudent thesis
Foreground segmentation is a common first step in tracking and surveillance applications. The purpose of foreground segmentation is to provide later stages of image processing with an indication of where interesting data can be found. This thesis is an investigation of how foreground segmentation can be performed in two contexts: as a pre-step to trajectory tracking and as a pre-step in indoor surveillance applications.
Three methods are selected and detailed: a single Gaussian method, a Gaussian mixture model method, and a codebook method. Experiments are then performed on typical input video using the methods. It is concluded that the Gaussian mixture model produces the output which yields the best trajectories when used as input to the trajectory tracker. An extension is proposed to the Gaussian mixture model which reduces shadow, improving the performance of foreground segmentation in the surveillance context.
Place, publisher, year, edition, pages
2010. , 62 p.
Foreground Segmentation, Background Subtraction, Gaussian Mixture Models, Codebook, Tracking, Shadow Detection, Auto Exposure
Computer Vision and Robotics (Autonomous Systems)
IdentifiersURN: urn:nbn:se:liu:diva-52544ISRN: LiTH-ISY-EX–10/4299–SEOAI: oai:DiVA.org:liu-52544DiVA: diva2:285807
Subject / course
Computer Vision Laboratory
2009-12-18, 10:00 (English)