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Making Time-of-Flight range imaging cameras applicable for human-machine-interaction by depth correction

机译:通过深度校正使飞行时间范围成像相机适用于人机交互

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For various applications, such as object recognition or tracking and especially when the object is partly occluded or articulated as in human-machine-interaction scenarios, 3D information is crucial for the robustness of the application. Recently sensor had been developed that acquire distance information based Time-of-Flight (ToF) principle and for which distance errors based on different causes can be observed. There are several technologies present for range imaging such as the Photo Mixer Device (PMD) working on modulated, incoherent infrared light or by using the depth imprint of an emitted light pulse by fast shuttering. This article presents a distance calibration approach for distance sensing which handles objects with different Lambertian reflectance properties because different albedos strongly affect the distance offsets. It combines the depth noise estimate and the intensity for a reflectivity estimate. The calibration results of the proposed method excel the results of other known methods due to the fact that they mostly do not incorporate the major effect of object reflectivity for the depth correction. In particular with objects with unknown reflectance properties a significant reduction of the error is achieved.
机译:对于各种应用程序,例如对象识别或跟踪,尤其是当对象在人机交互场景中被部分遮挡或铰接时,3D信息对于应用程序的鲁棒性至关重要。最近,已经开发出一种传感器,该传感器获取基于飞行时间(ToF)原理的距离信息,并且可以观察到基于不同原因的距离误差。目前存在多种用于距离成像的技术,例如在调制的,非相干红外光上工作的光电混合器(PMD),或通过快速快门使用发射光脉冲的深度印记的技术。本文提出了一种用于距离感应的距离校准方法,该方法可以处理具有不同朗伯反射特性的物体,因为不同的反照率会严重影响距离偏移。它结合了深度噪声估计和强度,以进行反射率估计。所提出的方法的校准结果优于其他已知方法的结果,这是由于以下事实:它们大部分没有结合用于深度校正的物体反射率的主要影响。特别是对于具有未知反射率特性的物体,可以显着降低误差。

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