Evaluation of Real-Time Single-Object Tracking Algorithms in a Non-Stationary Robotic Agent
Visual object tracking is a fairly easy task for humans but a challenging problem in computer vision and thereby in humanoid implementation. Most of the existing object tracking evaluations are performed with prerecorded video footage, often with a stationary camera. This is not representative of a humanoid platform. The aim of the present thesis was to evaluate different object tracking algorithm