This paper explores the application of event-based cameras in the domains of image segmentation and motion estimation. These cameras offer a groundbreaking technology by capturing visual information as a continuous stream of asynchronous events, departing from the conventional frame-based image acquisition. We introduce a Generalized Nash Equilibrium based framework that leverages the temporal and spatial information derived from the event stream to carry out segmentation and velocity estimation. To establish the theoretical foundations, we derive an existence criteria and propose a multi-level optimization method for calculating equilibrium. The efficacy of this approach is shown through a series of experiments.

翻译：本文探讨了事件相机在图像分割与运动估计领域的应用。这类相机通过将视觉信息捕获为异步事件的连续流，突破了传统的基于帧的图像采集方式，是一项开创性技术。我们提出了一种基于广义纳什均衡的框架，利用事件流中提取的时空信息进行分割与速度估计。为奠定理论基础，我们推导了存在性准则，并提出了一种用于计算均衡的多层次优化方法。通过一系列实验验证了该方法的有效性。