Title :
Video moving object detection based on desicion fusion
Author :
Yangcheng Guo ; Deqiang Han ; Yi Yang
Author_Institution :
Inst. of Integrated Autom., Xi´an Jiaotong Univ., Xi´an, China
Abstract :
The process of video moving object detection always has some uncertainty in the pixel´s decision belonging to foreground or background. In this paper, we attempt to resolve such uncertainty problems by using multiple methods based on decision fusion. First, we convert the decision outputs of the Gaussian Mixture Model (GMM), median filter and codebook three single methods into the membership outputs, respectively. Then, we fuse these three methods by using different decision fusion rules to obtain the detection results. Experimental results show that the fusion-based-detection method has better detection performance.
Keywords :
Gaussian processes; median filters; mixture models; object detection; video signal processing; GMM; Gaussian mixture model; codebook; decision fusion; median filter; multiple methods; pixel decision; video moving object detection; Gaussian mixture model; Image segmentation; Matched filters; Object detection; Probability density function; Uncertainty; decision; fusion-based-detection; membership; uncertainty; video moving object detection;
Conference_Titel :
Mechatronics and Control (ICMC), 2014 International Conference on
Print_ISBN :
978-1-4799-2537-7
DOI :
10.1109/ICMC.2014.7231733