Vision-based context and height estimation for 3D indoor location

Bashir Kazemipur, Z. Syed, J. Georgy, N. El-Sheimy
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引用次数: 7

Abstract

Today's smartphones are powerful devices whose continually increasing processing power and wide array of sensors make them well suited for use as personal navigation devices. In the absence of information from the Global Navigation Satellite System (GNSS), the onboard inertial sensors can be used to provide a relative navigation solution. However, these onboard inertial sensors suffer from the effects of different sensor errors which cause the inertial-only solution to deteriorate rapidly. As such, there is a need to constrain the inertial positioning solution when long term navigation is needed. GNSS positions and velocities, and WiFi positions are the most important forms of updates available for the inertial solution. However, updates from these two sources depend on external signals and may not always be available. A rich source of information about the outside world can be obtained using the device's camera. Nearly all devices have at least one camera which has thus far been largely neglected as a navigation aid for these mobile devices. There are many indoor scenarios that require accurate height estimates. Traditionally, barometers have been used to provide height information. However, not all mobile devices that are equipped with inertial sensors are also equipped with a barometer. As nearly all devices are equipped with at least one camera, it is our aim to use information from the camera to aid the inertial-only solution with appropriate height estimates. Different pattern analysis techniques are used to identify the different scenarios. The results are presented for the following common use cases: (1) single floor texting mode, (2) stairs texting mode, (3) single floor calling mode, (4) stairs calling mode, and (5) fidgeting the phone while standing still on a single floor (i.e. “fidgeting”). For each of these use cases, first the context will be determined and then the relevant information will be used to calculate the height accordingly. This work is patent pending.
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基于视觉的三维室内定位环境和高度估计
今天的智能手机是功能强大的设备,其不断增强的处理能力和广泛的传感器阵列使其非常适合用作个人导航设备。在缺乏全球导航卫星系统(GNSS)信息的情况下,机载惯性传感器可用于提供相对导航解决方案。然而,这些机载惯性传感器受到不同传感器误差的影响,导致惯性解迅速恶化。因此,当需要长期导航时,需要约束惯性定位解决方案。GNSS位置和速度以及WiFi位置是惯性解决方案中最重要的更新形式。然而,来自这两个源的更新依赖于外部信号,可能并不总是可用的。使用该设备的摄像头可以获得有关外部世界的丰富信息来源。几乎所有的设备都至少有一个摄像头,迄今为止,它作为这些移动设备的导航辅助在很大程度上被忽视了。有许多室内场景需要精确的高度估计。传统上,气压计被用来提供高度信息。然而,并非所有配备惯性传感器的移动设备都配备了气压计。由于几乎所有设备都配备了至少一个摄像头,因此我们的目标是使用摄像头的信息来帮助获得具有适当高度估计的纯惯性解决方案。使用不同的模式分析技术来识别不同的场景。结果显示了以下常见用例:(1)单层短信模式,(2)楼梯短信模式,(3)单层呼叫模式,(4)楼梯呼叫模式,以及(5)在单层楼上站着不动时摆弄手机(即“坐立不安”)。对于这些用例中的每一个,首先将确定上下文,然后使用相关信息来计算相应的高度。这项工作正在申请专利。
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