Event cameras are promising devices for lowlatency tracking and high-dynamic range imaging. In this paper,we propose a novel approach for 6 degree-of-freedom (6-DoF)object motion tracking that combines measurements of eventand frame-based cameras. We formulate tracking from highrate events with a probabilistic generative model of the eventmeasurement process of the object. On a second layer, we refinethe object trajectory in slower rate image frames through directimage alignment. We evaluate the accuracy of our approach inseveral object tracking scenarios with synthetic data, and alsoperform experiments with real data.
翻译:活动相机是低延度跟踪和高动态射程成像的有希望的装置。在本文中,我们提出了6度自由(6-DoF)物体运动跟踪的新办法,该办法结合对事件和基底摄影机的测量。我们从高频事件和物体事件测量过程的概率基因化模型进行跟踪。在第二层,我们通过直接图像对齐来改进低速图像框中的天体轨迹。我们用合成数据来评估我们方法中无数物体跟踪情景的准确性,用真实数据来评估实验的精确性。