Title :
Commentary Paper 1 on "On Stable Dynamic Background Generation Technique Using Gaussian Mixture Models for Robust Object Detection"
Author :
Visentini, Ingrid
Author_Institution :
Univ. of Udine, Udine, Italy
Abstract :
In this paper a technique for motion detection that exploits the Gaussian mixture models (GMM) and basic background subtraction (BBS) is proposed. For every frame, each pixel is modeled with almost K Gaussian distributions. All the existing GMM based techniques use a threshold to set a priori the number of Gaussians to represent the background. The proposed approach avoids setting this threshold. The results show the effectiveness of the novel approach on benchmarks test sets sequences.
Keywords :
Gaussian distribution; Gaussian processes; object detection; Gaussian distributions; Gaussian mixture models; basic background subtraction; robust object detection; stable dynamic background generation technique; Benchmark testing; Gaussian distribution; Motion detection; Object detection; Robustness; Signal generators; Surveillance; Videoconference; Weaving;
Conference_Titel :
Advanced Video and Signal Based Surveillance, 2008. AVSS '08. IEEE Fifth International Conference on
Conference_Location :
Santa Fe, NM
Print_ISBN :
978-0-7695-3341-4
Electronic_ISBN :
978-0-7695-3422-0
DOI :
10.1109/AVSS.2008.55