Reflection Aware Visual Simultaneous Localization and Mapping (RA-vSLAM)

反射感知视觉同步定位和建图 (RA-vSLAM)

• 批准号: 2435656
• 金额: --
• 依托单位: CARDIFF UNIVERSITY
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2020
• 资助国家: 英国
• 起止时间: 2020 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2435656
• 关键词: Reflection; Aware; Visual; Simultaneous; Localization

The project in computer vision and robotics will research the impact of visual reflections in simultaneous localization and mapping (SLAM). Reflections are ubiquitous in our environment, and are utilised by our vision system to extend the field of view. An example is the use of rear view mirrors on cars. Visual reflections, although provide only 'subtle' information, bring flexibility to our visual perception of the environment. However, such information has not been utilized in computer vision systems. SLAM is a technique originally developed for robotics applications. Visual SLAM (vSLAM) allows a mobile device to incrementally build a map of its environment and localise itself within that map, using only visual information. Even the state-of-the-art vSLAM solutions are based on the assumption that the scenes captured are real and direct, without consideration of those 'virtual' images resulted from reflections. It is an interesting question whether and how reflections can be used to improve the flexibility and robustness of current vSLAM solutions. The answer to it will find important applications in robot navigation, various autonomous systems, VR/AR, etc. This project will take a step forward to answer this question by considering planar and mirror reflections in indoor vSLAM, and aims to understand the influence of visual reflections in current vSLAM solutions, and develop a reflection-aware vSLAM solution for more flexible and robust mapping and localisation. To achieve the aim, several key aspects will be researched in the project, including analysis of the robustness of current visual SLAM solutions to mirror reflections, exploration of different approaches to detect and localize mirror planes, and utilise the detected reflections for 3D localization and mapping. Evaluation of the developed algorithms may be carried out in both simulation and in real-world.

计算机视觉和机器人项目将研究视觉反射在同时定位和映射（SLAM）中的影响。反射在我们的环境中无处不在，并被我们的视觉系统用来扩展视野。一个例子是在汽车上使用后视镜。视觉反射，虽然只提供“微妙”的信息，但给我们对环境的视觉感知带来了灵活性。然而，这些信息尚未在计算机视觉系统中得到利用。SLAM是最初为机器人应用开发的技术。视觉SLAM（vSLAM）允许移动终端仅使用视觉信息来递增地构建其环境的地图并将其自身定位在该地图内。即使是最先进的vSLAM解决方案也是基于这样的假设，即所捕获的场景是真实的且直接的，而不考虑由反射产生的那些“虚拟”图像。反射是否以及如何用于提高当前vSLAM解决方案的灵活性和鲁棒性是一个有趣的问题。该项目将通过考虑室内vSLAM中的平面和镜面反射来回答这个问题，旨在了解当前vSLAM解决方案中视觉反射的影响，并开发一种反射感知的vSLAM解决方案，以实现更灵活，更强大的映射和定位。为了实现这一目标，该项目将研究几个关键方面，包括分析当前视觉SLAM解决方案对镜面反射的鲁棒性，探索检测和定位镜面的不同方法，并利用检测到的反射进行3D定位和映射。所开发的算法的评估可以在模拟和现实世界中进行。