Attentive sensor for dynamic scene analysis

传统的机器视觉系统采用单个摄像机，视场相对较小。然而，诸如运动摄像之类的应用需要更大的视野来监视扩展的环境，以及需要高分辨率来解决重要的细节(例如，冰球在冰球中的位置)。这两个要求是相互冲突的，不能用单个相机以最佳方式满足。我们的实验室开发了注意力传感技术(加拿大专利2386347，美国专利7130490)，通过紧密结合两个不同视场的相机系统来满足这些要求。该系统集成了一个宽视野(FOV)摄像机，提供对更大环境的连续监控，以及一个窄视野云台摄像机，可以使用专门的计算机视觉和控制软件定向到感兴趣的对象。因此，该系统在更广泛的场景的整个上下文中传递来自关键目标(例如，人脸)的详细信息。拟议项目的目标是设计、建造、评估和改进这项技术的下一代商业原型，用于体育录像、远程学习和地面和无人驾驶飞行器平台的监视等新兴应用。

Traditional machine vision systems employ a single camera with relatively small field of view (FOV). However, applications such as sports videography require a larger field of view to monitor an extended environment, as well as high resolution to resolve important details (e.g., the location of the puck in ice hockey). These two requirements are conflicting and cannot be met optimally with a single camera. Our laboratory has developed attentive sensing technology (Canadian Patent 2386347, US Patent 7130490) that meets these requirements by closely coupling two camera systems with different fields of view. The system integrates a wide field-of-view (FOV) camera providing continuous monitoring of the larger environment with a narrow FOV pan-tilt camera that can be directed to objects of interest using specialized computer vision and control software. The system thus delivers detailed information from critical targets (e.g., human faces) in the full context of the wider scene. The goal of the proposed project is to design, build, evaluate and refine next-generation commercial prototypes of this technology for emerging applications such as sports videography, remote learning and surveillance from terrestrial and unmanned aerial vehicle platforms.