ISAR Signal Tracking and High-Resolution Imaging by Kalman Filtering

Road Tracking from High resolution IRS And IKONOS Images Using Unscented Kalman Filtering

A typical way to update map is to compare recent satellite images with existing map data, detect new roads and add them as cartographic entities to the road layer. At present image processing and pattern recognition are not robust enough to automate the image interpretation system feasible. For this reason we have to develop an image interpretation system that rely on human guidance. More impor...

Visual Tracking by Adaptive Kalman Filtering and Mean Shift

A method for object tracking combining the accuracy of mean shift with the robustness to occlusion of Kalman filtering is proposed. At first, an estimation of the object’s position is obtained by the mean shift tracking algorithm and it is treated as the observation for a Kalman filter. Moreover, we propose a dynamic scheme for the Kalman filter as the elements of its state matrix are updated o...

Tracking and Kalman Filtering Made Easy

Extended Object Tracking Using Mixture Kalman Filtering

This paper addresses the problem of tracking extended objects. Examples of extended objects are ships and a convoy of vehicles. Such kind of objects have particularities which pose challenges in front of methods considering the extended object as a single point. Measurements of the object extent can be used for estimating size parameters of the object, whose shape is modeled by an ellipse. This...

Unscented Kalman Filtering for Articulated Human Tracking

We present an articulated tracking system working with data from a single narrow baseline stereo camera. The use of stereo data allows for some depth disambiguation, a common issue in articulated tracking, which in turn yields likelihoods that are practically unimodal. While current state-of-the-art trackers utilize particle filters, our unimodal likelihood model allows us to use an unscented K...