A flexible gaze tracking algorithm evaluation workbench

Abstract

The development of gaze tracking algorithms is very much bound to the specific setup and properties of the respective system they are used in. This makes it hard e. g. to compare their performance. We propose Gazelnut, a modular system to ease the development and comparison of gaze tracking algorithms, which also makes it independent from the permanent access to specific hardware. Building on the message passing architecture of the "robot operating system" (ROS) the system provides a flexible base to record and replay sessions, record the input from multiple cameras, run exchangeable algorithms on such sessions, store their individual results on the recorded (or live) scene, run different algorithms in parallel to compare their results and attach additional diagnostic modules to the running system.