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Abandoned Object Detection Based on Video Image Sequences

Author: LiZuo
Tutor: FangMin
School: Xi'an University of Electronic Science and Technology
Course: Applied Computer Technology
Keywords: Dual background difference Split contour integration Kalman filtering Regional centroid tracking Support Vector Machine
CLC: TP391.41
Type: Master's thesis
Year: 2010
Downloads: 54
Quote: 0
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Abstract


With the rapid development of highways and tunnels , and the resulting traffic accidents increased spilled material events occur frequently as a traffic incident , it caused traffic accidents and the potential security risks has become an urgent problem . How timely and accurate detection of the spilled material events , as soon as possible to exclude security risks , safeguard the smooth highway and tunnel safety has become the focus of attention . Analysis related to the lost property detection algorithm based on the dual background Lost Property - based detection method applied to the spilled material traffic incident detection , and suggest improvements , combined with support vector machines ( Support Vector Machine SVM) classifier for short results to identify and eliminate erroneous judgment , accurately detect the events of the spilled material , in order to adapt to the Highway Traffic this particular application environment . Moving target detection and track moving objects and tossed objects from detection is divided into three major parts . First , in the analysis of the moving target detection algorithm based on background subtraction method , in order to ensure the timeliness of the operation . Extracted by image preprocessing , background and updates , background subtraction , shadow elimination steps to complete the detection of moving targets . The split contour fusion algorithm fusion experiments show the contour detection split after the fusion of the split contour detection accuracy has been greatly improved . Secondly , the use of two commonly used motion tracking algorithm , Kalman filtering based on the area centroid tracking method , at the same time gives the instantaneous speed and traffic volume and traffic parameters calculated , create and update a moving target file , the moving target real-time tracking . Finally, on the basis of the work in the front , the application to the spilled material event the Lost Property detection method based on dual background detection . In order to adapt to the special environment of the Highway Traffic using SVM classification and recognition of the moving target , classified as non- car moving target detection to eliminate false judgment . Experiments show that the combined SVM classifier results in improved the Lost Property detection method based on dual background applied to the spilled material traffic incident detection Highway Traffic special environment can adapt well to achieve a good detection results .

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CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer applications > Information processing (information processing) > Pattern Recognition and devices > Image recognition device
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