How Many Events are Needed for One Reconstructed Image Using an Event Camera?
Keywords: Event Camera, Event-based Vision, Image Reconstruction
Abstract. Event cameras offer significant advantages over traditional cameras, including high temporal resolution, high dynamic range, and low power consumption. However, reconstructing images from the asynchronous events generated by these cameras presents unique challenges. This paper investigates the optimal number of events needed for high-quality image reconstruction using event cameras. We evaluate two primary reconstruction strategies—fixed time window and fixed number of events—across various dynamic and static scenes. Our study includes scenarios with different lighting conditions and camera movements. Using the state-of-the-art E2VID algorithm, we perform both qualitative and quantitative analyses of the reconstructed images, comparing them with reference frames from a traditional RGB camera. Our results demonstrate the trade-offs between temporal resolution and image quality for each reconstruction strategy, providing insights into the optimal settings for different applications. This research offers practical guidelines for selecting appropriate reconstruction parameters to achieve the better image quality from event cameras.