LAUSR

Online single target tracking (OSTT) is a prominent topic in normal surveillance environments for security and transportation applications. However, OSTT comparative analysis is seriously under-investigated in the context of wide area motion imagery (WAMI) although its importance keeps rising with the popularity of the unmanned aerial vehicles. In this work, we make several efforts toward WAMI tracking analysis. First, we propose a new WAMI OSTT benchmark dataset, named WAMI-226, which consists of 100 image frames and 226 targets. This new benchmark dataset brings together research challenges including low frame rate, low resolution, and low contrast. Second, we evaluate 20 existing online trackers for WAMI tracking scenarios. Third, by combining the basic appearance model, background subtraction and high-order motion (HoM) affinity, we develop a novel normalized cross correlation HoM (NCC-HoM) tracking algorithm for WAMI OSTT. The experimental results show that the proposed NCC-HoM method achieves significant improvements for both target initialization and online tracking. Thus, NCC-HoM serves as a new baseline algorithm for the WAMI-226 benchmark.