Title :
Motion Object Detection Based on Adaptive Mixture Gaussian Model and Four-Frame Subtraction
Author :
Qinghua Ji ; Suping Yu
Author_Institution :
Dept. of Inf. Sci. & Technol., Donghua Univ., Shanghai, China
Abstract :
In view of background subtraction is influenced by the light and the frame difference is easily affected by double shadow and hole phenomenon in target detection, a motion detection algorithm based on adaptive mixture gaussian model and four-frame subtraction using the dynamic threshold is proposed. In this paper, in order to minimize the negative influences of noise and hole, connected region domain analysis and hole filling algorithm are introduced. The experimental result shows that the algorithm has preferable adaptive performance to the scene with the detection of the moving target accurately.
Keywords :
Gaussian processes; image motion analysis; object detection; adaptive mixture Gaussian model; background subtraction; connected region domain analysis; double shadow; dynamic threshold; four-frame subtraction; frame difference; hole filling algorithm; hole phenomenon; motion object detection algorithm; Adaptation models; Algorithm design and analysis; Computer vision; Dynamics; Heuristic algorithms; Lighting; Object detection; adaptive mixture Gussian model; connected region domain analysis; dynamic threshold; four-frame subtraction; motion target detection;
Conference_Titel :
Computational and Information Sciences (ICCIS), 2013 Fifth International Conference on
Conference_Location :
Shiyang
DOI :
10.1109/ICCIS.2013.318