Moving Object Detection Based on Two-Staged Background Subtraction Approach
Date Issued
2009
Date
2009
Author(s)
Su, Shu-Te
Abstract
Moving object detection based on two-staged background subtraction approach is proposed in this thesis. Background subtraction in image sequence is a popular approach for detecting moving objects, especially in a relatively static scene. However, there are some problems for background subtraction approach, such as the scene with varying illumination, the new static object in the background, and the captured frame with noise that caused by environment or camera. Moreover, sometimes the results in moving object detection have false detections due to near color in corresponding pixels of moving object and background. To solve above-mentioned problems, Two-Staged Background Subtraction (Two-StaBaS) approach is then proposed. The first stage is background modeling and background subtraction, the suggested background is Improved Running Average Background (IRAB). IRAB shows its improvements on the first three above-mentioned problems. The second stage is the modification of detection errors in the first stage, namely, it solves the near color problem. Background subtraction based on the weighting map in moving object candidate region, a number of false detections in background subtraction approach decreases. Finally, two-staged background subtraction approach has the advantages of fast computational speed, low memory requirement, and good accuracy for detecting moving objects.
Subjects
moving object detection
background subtraction
background update
auto-thresholding algorithm
foreground analysis
shadow detection
Type
thesis
File(s)![Thumbnail Image]()
Loading...
Name
ntu-98-R96921047-1.pdf
Size
23.32 KB
Format
Adobe PDF
Checksum
(MD5):55fa2d5cd3c95e8cd5ac769f84e7a622