Patch-based adaptive weighting with segmentation and scale (PAWSS) for visual tracking in surgical video.

ABSTRACT: Vision-based tracking in an important component for building computer assisted interventions in minimally invasive surgery as it facilitates estimation of motion for instruments and anatomical targets. Tracking-by-detection algorithms are widely used for visual tracking, where the problem is treated as a classification task and a tracking target appearance model is updated over time using online learning. In challenging conditions, like surgical scenes, where tracking targets deform and vary in scale, the update step is prone to include background information in model appearance or to lack the ability to estimate change of scale, which degrades the performance of classifier. In this paper, we propose a Patch-based Adaptive Weighting with Segmentation and Scale (PAWSS) tracking framework th

SUBMITTER: Du X 

PROVIDER: S-EPMC6988132 | biostudies-literature | 2019 Oct

REPOSITORIES: biostudies-literature