Fast Image-Based Tracking by Selective Pixel Integration

Abstract

We provide a fast algorithm to perform image-based tracking, which relies on the selective integration of a small subset of pixels that contain a lot of information about the state variables to be estimated. The resulting dramatic decrease in the number of pixels to process results in a substantial speedup of the basic tracking algorithm. We have used this new method within a surveillance application, where it will enable new capabilities of the system, i.e. real-time, dynamic background subtraction from a panning and tilting camera.