# Exploring the Potential of Event Camera Imaging for Advancing Remote Pupil-Tracking Techniques
## 1 Introduction  
Pupil tracking is a fundamental task in computer vision, human-computer interactions, virtual reality (VR), and augmented reality (AR) display systems. It plays a crucial role in enabling various applications, including gaze estimation [1], attention tracking [2], biometric identification [3], and Autostereoscopic three-dimensional (3D) displays, such as AR 3D head-up displays (HUDs) [4]. Eye pupil tracking is also useful in psychology and medicine. Researchers have used it to identify conditions, like stress, by studying how the eyes move and other related body signals [5]. Extensive research has been conducted on head-mounted eye-pupil tracking, a close-range eye-tracking technology primarily designed for wearable devices [6; 7; 8]. Additionally, remote eye-tracking has also garnered significant attention in the research community. Remote pupil tracking enables the monitoring and analysis of eye movements from a distance without requiring any physical contact with the user. This non-intrusive technology finds applications in various fields, including human-computer interactions [9], psychological studies [10], Autostereoscopic 3D displays [11], and AR 3D HUDs in automobiles [4], offering valuable insights into users' visual attention and cognitive processes. The advancements in remote eye-tracking techniques have paved the way for more practical and non-intrusive implementations inreal-world scenarios. While previous studies have extensively utilized traditional frame-based camera systems, sometimes with the integration of near-infrared (NIR) light, for remote pupil-tracking tasks [11; 12], they inherently possess certain limitations, particularly in capturing fast and subtle eye movements that are vital for comprehending cognitive processes and human behavior. Recently, the emergence of event camera imaging has piqued the interest of the computer vision community due to its unique capabilities for dynamic vision tasks. Event cameras asynchronously capture pixel-level intensity changes, or events, triggered by significant changes in the scene, such as motion. This novel sensing modality offers distinct advantages over conventional frame-based cameras, including a high temporal resolution, low latency, and low power consumption. These properties make event cameras highly attractive for capturing fast eye movements, such as rapid eye movements and subtle eye motions, which are often missed or blurred in frame-based systems [13]. One of the key characteristics of event cameras is their ability to represent motion through positive and negative pixel intensity changes. Positive events represent increases in intensity, while negative events signify decreases. As a result, event cameras provide a sparse representation of the scene, focusing solely on the changes occurring in the environment when motion occurs (Figure 1). This unique feature allows event cameras to excel in capturing dynamic scenes with reduced redundancy and minimized motion blur, making them particularly well-suited for tasks, like pupil tracking, where fast eye movements are critical for accurate analysis [13]. Figure 1: Examples of event camera imaging (**left**) capturing different levels of motion compared to frame-based Complementary Metal-Oxide-Semiconductor (CMOS) camera (**right**). The 1 st row shows examples of minimal motion, the 2 nd row shows subtle motion, and the 3 rd row shows large motion with verifiable eye shape. As depicted in the examples, event cameras effectively capture the pixel-level intensity changes corresponding to motion, providing a clear representation of dynamic events and enhancing the accuracy of pupil-tracking algorithms. In this paper, considering the potential of event camera imaging, we focus on developing remote pupil-tracking techniques using event cameras for Autostroscopic 3D displays and AR 3D HUDs. Using knowledge from traditional frame-based eye-tracking, our primary goal is to assess the viability of pupil tracking using event cameras.