PERFORMANCE EVALUATION OF MOVING OBJECT DETECTION AND TRACKING ALGORITHM FOR OUTDOOR SURVEILLANCE USING MODIFIED GMM
Journal: International Journal of Engineering Sciences & Research Technology (IJESRT) (Vol.6, No. 7)Publication Date: 2017-07-30
Authors : Navneet S. Ghedia; C.H. Vithalani; Ashish Kothari;
Page : 215-223
Keywords : visual monitoring system; adaptive thresholding; background modelling; foreground detection; mixture of Gaussians;
Abstract
Robust Visual Monitoring system that detects and analyze activities based on human, vehicle or animal detection and tracking assures good surveillance. This paper focuses on two dimensional object detection and tracking using Modified Gaussian mixture model (GMM), Adaptive threshold and prediction filtering. Our proposed approach improves learning rate of model for the various constraint like clutter background, light variations, slow and fast moving objects, entering or removed objects, partial occlusion. Our aim is to design such an algorithm which works well on outdoor video sequences.
Other Latest Articles
- A REVIEW OF RARE-EARTH IONS DOPED UPCONVERSION PROCESS IN SOLAR CELLS
- BEHAVIOUR OF STEEL FIBER REINFORCED CONCRETE
- AN EFFICIENT JOINT ENCRYPTION AND COMPRESSION USING HOP AND PERMUTATION
- COMPARATIVE STUDY OF LOW RISE RESIDENTIAL BUILDINGS INTERMS OF PLATE STRESS AND ECONOMIC EVALUATION WITH SOLID SLAB AND RIBBED SLAB: STATIC ANALYSIS
- HAZARD ANALYSIS AND RISK ASSESSMENT IN THERMAL POWER PLANT
Last modified: 2017-07-06 18:54:32