Visual Models - Application to Situational Awareness

我的研究解决了计算机视觉的表示问题，特别是如何从传感器网络捕获信息，并创建真实反映一段时间环境的计算机模型。在这项提案中有3个具体的子项目。第一个涉及为与人类协同工作的机器人助手提供情境感知。对象(人+机器)被表示为铰接式3D模型，实时跟踪它们在现实世界中的对应对象。科学的焦点是如何捕获动态行为并对其进行建模，以便系统能够识别或控制每个乘客的活动。在之前与通用汽车研究的基础上，目标是在机器人助手中嵌入更强大和更可靠的情景感知，从而使实际实施成为可能。如果这一愿景成功，未来的装配线将由人类-机器人团队合作制造产品，极大地提高生产率，并使加拿大在全球市场上保持竞争力。

My research addresses the problem of representations for computer vision, specifically how to capture information from a sensor network and create computer models that faithfully reflect an environment over time. There are 3 specific sub-projects within this proposal. The first deals with providing situational awareness for a robotic assistant working in conjunction with a human. Objects (humans + machines) are represented as articulated 3D models that track their real world counterparts in real time. The scientific focus is how to capture and model dynamic behavior so that the system can identify or control the activities of each occupant. Following on previous work with GM research, the goal is to embed robotic assistants with more powerful and reliable situational awareness so that practical implementations become possible. If this vision is successful, future assembly lines will be comprised of human-robot teams collaborating to manufacture products, greatly scaling up productivity and allowing Canada to remain competitive in the global marketplace.