A parallel spatiotemporal saliency and discriminative online learning method for visual target tracking in aerial videos.

ABSTRACT: Visual tracking in aerial videos is a challenging task in computer vision and remote sensing technologies due to appearance variation difficulties. Appearance variations are caused by camera and target motion, low resolution noisy images, scale changes, and pose variations. Various approaches have been proposed to deal with appearance variation difficulties in aerial videos, and amongst these methods, the spatiotemporal saliency detection approach reported promising results in the context of moving target detection. However, it is not accurate for moving target detection when visual tracking is performed under appearance variations. In this study, a visual tracking method is proposed based on spatiotemporal saliency and discriminative online learning methods to deal with appearance variati

SUBMITTER: Aghamohammadi A 

PROVIDER: S-EPMC5811006 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature