Visual Object Tracking in Spherical 360° Videos: A Bridging Approach

Abstract

We present a novel approach for adapting existing visual object trackers (VOT) to work for equirectangular video, utilizing image reprojection. Our system can easily be integrated with existing VOT algorithms, significantly increasing the accuracy and robustness of tracking in spherical 360° environments without requiring retraining. Our adapted approach involves the orthographic projection of a subsection of the image centered around the tracked object each frame. Our projection reduces the distortion around the tracked object each frame, allowing the VOT algorithm to more easily track the object as it moves.