This work presents an approach to detect moving objects from Unmanned Aerial Vehicles (UAV). A common frame- work for most of the existing techniques is using image reg- istration to warp consecutive frames as an ego-motion com- pensation step and applying frame differencing to detect the moving objects. Assuming a planar scene, we propose the exploitation of telemetry information available from Global Positioning and Inertial Navigation Systems (GPS/INS) to estimate a similarity transformation matrix that would map the image points from one frame to another. In this work, we show that the telemetry-based image registration com- bined with global registration methods produces more ac- curate results than the traditional image registration tech- niques in case of a scene with poor or no texture. To segment the moving objects, we employ the probabilistic background modelling method with mixture of Gaussian distributions.    «

This work presents an approach to detect moving objects from Unmanned Aerial Vehicles (UAV). A common frame- work for most of the existing techniques is using image reg- istration to warp consecutive frames as an ego-motion com- pensation step and applying frame differencing to detect the moving objects. Assuming a planar scene, we propose the exploitation of telemetry information available from Global Positioning and Inertial Navigation Systems (GPS/INS) to estimate a similarity transformation...    »