SwitchHit：一种基于概率互补的切换系统，用于改进变化环境中的视觉位置识别
SwitchHit: A Probabilistic, Complementarity-Based Switching System for Improved Visual Place Recognition in Changing Environments
摘要：
视觉位置识别是计算机视觉和机器人学的一项基础性研究，主要是基于视觉信息的位置识别问题。由于天气和季节变化等原因，视角和外观的变化使这项任务具有挑战性。目前，还没有通用的VPR技术可以在所有类型的环境中，在各种机器人平台上，以及在广泛的视角和外观变化下工作。最近的工作表明，通过评估某些特定VPR数据集的互补性，可以智能地组合不同的VPR方法，以实现更好的性能。然而，这需要地面实况信息（正确匹配），当机器人部署在真实世界场景中时，这是不可用的。此外，并行运行多个VPR技术对于资源受限的嵌入式平台可能是禁止的。为了克服这些局限性，本文提出了一种基于概率互补的切换VPR系统，SwitchHit。我们提出的系统由多个VPR技术，但是，它并不简单地运行所有的技术在一次，而是预测正确匹配的概率为传入的查询图像和动态切换到另一个互补的技术，如果正确匹配的查询的概率低于一定的阈值。这种创新性地使用多种VPR技术，使我们的系统比其他采用蛮力和同时运行多种VPR技术的组合VPR方法更有效和鲁棒。因此，使其更适合于资源受限的嵌入式系统，并实现了系统中任何单独的VPR方法通过独立运行所能实现的整体优越性能。
英文摘要：
Visual place recognition (VPR), a fundamental task in computer vision and robotics, is the problem of identifying a place mainly based on visual information. Viewpoint and appearance changes, such as due to weather and seasonal variations, make this task challenging. Currently, there is no universal VPR technique that can work in all types of environments, on a variety of robotic platforms, and under a wide range of viewpoint and appearance changes. Recent work has shown the potential of combining different VPR methods intelligently by evaluating complementarity for some specific VPR datasets to achieve better performance. This, however, requires ground truth information (correct matches) which is not available when a robot is deployed in a real-world scenario. Moreover, running multiple VPR techniques in parallel may be prohibitive for resource-constrained embedded platforms. To overcome these limitations, this paper presents a probabilistic complementarity based switching VPR system, SwitchHit. Our proposed system consists of multiple VPR techniques, however, it does not simply run all techniques at once, rather predicts the probability of correct match for an incoming query image and dynamically switches to another complementary technique if the probability of correctly matching the query is below a certain threshold. This innovative use of multiple VPR techniques allow our system to be more efficient and robust than other combined VPR approaches employing brute force and running multiple VPR techniques at once. Thus making it more suitable for resource constrained embedded systems and achieving an overall superior performance from what any individual VPR method in the system could have by achieved running independently.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
