R. Pelapur, K. Palaniappan, and G. Seetharaman

9th IEEE Int. Conf. Advanced Video and Signal-Based Surveillance, 2012

wami, tracking, fmv, motion, features, dod

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Abstract

Visual feature-based tracking systems need to adapt to variations in the appearance of an object and in the scene for robust performance. Though these variations may be small for short time steps, they can accumu- late over time and deteriorate the quality of the match- ing process across longer intervals. Tracking in aerial imagery can be challenging as viewing geometry, cal- ibration inaccuracies, complex flight paths and back- ground changes combined with illumination changes, and occlusions can result in rapid appearance change of objects. Balancing appearance adaptation with sta- bility to avoid tracking non-target objects can lead to longer tracks which is an indicator of tracker robust- ness. The approach described in this paper can han- dle affine changes such as rotation by explicit orien- tation estimation, scale changes by using a multiscale Hessian edge detector and drift correction by using seg- mentation. We propose an appearance update approach that handles the ‘drifting’ problem using this adaptive scheme within a tracking environment that is comprised of a rich feature set and a motion model.