# Exploring the Potential of Event Camera Imaging for Advancing Remote Pupil-Tracking Techniques
## 2 Proposed Method
### Event Camera Imaging  
Event cameras stand out due to their asynchronous capture of events--instantaneous pixel intensity variations caused by scene changes. Their defining characteristics and suitability for eye-tracking applications are further detailed in this section. The key characteristic of event cameras is their asynchronous operation, where they capture pixel-level intensity changes, known as \"events,\" triggered by significant changes in the scene, such as motion. This unique sensing mechanism allows event cameras to react instantly to motion, leading to high temporal resolution and low latency. Unlike frame-based cameras that capture entire frames at fixed time intervals, event cameras produce events in real-time, providing a sparse and efficient representation of dynamic scenes. Another advantage of event cameras is their low power consumption. Traditional cameras often consume substantial power due to continuous image capture and processing, whereas event cameras only generate events when there is motion, significantly reducing power requirements. In terms of the data format, event cameras produce streams of events with precise timestamps, intensity changes, and corresponding pixel locations. This data format contrasts with conventional cameras, which produce sequences of static frames. Event camera data are highly suitable for capturing fast and subtle eye movements, such as rapid eye movements and subtle eye motions, which can be crucial for accurate eye tracking (Figure 2). By leveraging the unique capabilities of event camera imaging, we aim to enhance pupil-tracking performance, particularly in scenarios involving rapid eye movements and real-time applications. Figure 3 showcases the event camera used in our proposed method: the DAVIS 346 by Inivation [15]. This state-of-the-art event camera plays a crucial role in our research, enabling us to capture pixel-level intensity changes with exceptional precision. The DAVIS 346 event camera operates asynchronously, allowing it to respond instantaneously to motion events. Specifically, it processes a bandwidth of 12 million events per second, and its minimum latency is approximately 20 microseconds. Moreover, when converting these events for visualization purposes, they are typically aggregated to form event frames at a user-defined rate, similar to the event frame concept that accumulates events over a predefined interval to visualize them in a 2D image format. For our experiments, we chose to visualize these frames at 30 fps. The DAVIS 346 offers a resolution of 346 \(\times\) 260 pixels, a dynamic range of 120 dB, minimum latency of 20 \(\upmu\)s, and 180 mA power consumption at 5V DC. For our training and testing purposes, the images captured with the DAVIS 346 were resized to a resolution of 640 \(\times\) 480 pixels to optimize the performance of our algorithms. Figure 3: The event camera used in our proposed method: Inivation’s DAVIS 346 (**left**) [15]. The experimental setup for remote pupil tracking, demonstrating the distance range between the event camera imaging device and the user’s face, spanning from 50 to 100 cm (**right**). Figure 2: Illustration of the advantages of event cameras over conventional RGB-frame-based cameras. The 1 st row shows examples of RGB-frame-based images, and the 2 nd row shows corresponding images from the event camera images. (**a**) Rapid movement: while the RGB image shows motion blur due to swift movement, the event camera captures the eye’s shape without any motion blur. (**b**) Quick eye movement: demonstrating the capability of the event camera to capture rapid eye movements. During a fast blink, the RGB image lags and still depicts the eye as closed, whereas the event camera swiftly captures the moment, revealing the actual open state of the eye during this time. In addition to presenting the event camera itself, Figure 3 also illustrates the experimental setup we used for remote pupil tracking. The distance range between the event camera imaging device and the user's face spans from 50 to 100 cm.