This work expands upon state-of-the-art multiscale tracking based on compressive sensing (CT) by increasing the overall tracking accuracy. A pixelwise classification stage is incorporated in the CT-based tracker to obtain a relatively stable appearance model, by distinguishing object pixels from the background. In addition, we identify potential distracting regions that are used in a feedback strategy to handle occlusion and avoid drifting toward nearby regions with similar appearances. We evaluate our approach on several benchmark datasets to demonstrate its effectiveness with respect to the state-of-the-art tracking algorithms.
"Improved compressive tracking based on pixelwise learner," Journal of Electronic Imaging 27(1), 013003 (5 January 2018). https://doi.org/10.1117/1.JEI.27.1.013003
. Submission: Received: 5 April 2017; Accepted: 4 December 2017
Received: 5 April 2017; Accepted: 4 December 2017; Published: 5 January 2018