This paper introduces the first differentiable simulator of event streams, i.e., streams of asynchronous brightness change signals recorded by event cameras. Our differentiable simulator enables non-rigid 3D tracking of deformable objects (such as human hands, isometric surfaces and general watertight meshes) from event streams by leveraging an analysis-by-synthesis principle. So far, event-based tracking and reconstruction of non-rigid objects in 3D, like hands and body, has been either tackled using explicit event trajectories or large-scale datasets. In contrast, our method does not require any such processing or data, and can be readily applied to incoming event streams. We show the effectiveness of our approach for various types of non-rigid objects and compare to existing methods for non-rigid 3D tracking. In our experiments, the proposed energy-based formulations outperform competing RGB-based methods in terms of 3D errors. The source code and the new data are publicly available.
翻译:本文介绍了第一个不同的事件流模拟器, 即由事件相机记录的事件流的无同步亮度变化信号流。 我们不同的模拟器能够借助分析合成原则, 将事件流的变形物体( 如人手、 等离子表面和一般水密质)从事件流中进行非硬性 3D 跟踪 3D 跟踪 。 到目前为止, 基于事件 的跟踪和重建 3D 中非硬性物体( 如手和体), 要么 使用明确的事件轨迹或大型数据集进行处理 。 相反, 我们的方法不需要任何这样的处理或数据, 并且可以很容易地应用于事件流中。 我们展示了我们对各种非硬性物体( 如人体、 等) 3D 跟踪方法的实用性。 在我们的实验中, 拟议的基于能源的配方在3D 误差的 RGB 方法上超越了相竞争的 RGB 方法 。 源码和新数据是公开提供的 。