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Making Time-of-Flight Range Imaging Cameras applicable for Human-Machine-Interaction by Depth Correction

机译:制定飞行时间范围成像相机,适用于深度校正的人机交互

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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,例如对象识别或跟踪,尤其是当对象被部分地被封闭或被铰接,如在人机交互场景中,3D信息对于应用程序的鲁棒性至关重要。最近开发了传感器,其获得基于距离信息的飞行时间(TOF)原理,并且可以观察到基于不同原因的距离误差。存在若干技术用于范围成像,例如在调制的,非相干红外光或通过快速快门使用发射的光脉冲的深度压印器或通过快速快门使用的光混合器装置(PMD)。本文介绍了距离感测的距离校准方法,该方法处理具有不同兰布尔蒂氏反射特性的物体,因为不同的玻璃玻璃强烈影响距离偏移。它结合了深度噪声估计和反射率估计的强度。所提出的方法的校准结果擅长其他已知方法的结果,因为它们主要不包含对象反射率对深度校正的主要影响。特别是具有未知反射率特性的物体,实现了误差的显着降低。

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