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Real-time smart lighting control using human motion tracking from depth camera

机译:使用深度摄像机的人体运动跟踪进行实时智能照明控制

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摘要

A smart lighting system provides automatic control of lighting illumination and color temperature for high quality of life as well as energy savings in smart cities. A real-time activity understanding system with accurate human location estimation under varying illumination is required for smart lighting control, since comfortable lighting conditions vary according to human activities. This paper presents a real-time smart lighting control system using human location estimation based on inverse-perspective mapping of depth map images and activity estimation from location, heading direction, and height estimation of the moving person from multiple depth cameras. Lighting control based on estimated proximity to the specific activity area, distance to the target lighting area, and heading direction of the person provides an automatic activity-dependent lighting environment as well as energy savings. We implemented several activity modes such as study mode, dialog mode, and watching TV mode, and applied the proposed lighting control system to a living room lighting control with known furniture, electronics, and lighting locations using multiple Kinect depth cameras. The proposed model is based on localized proximity-based lighting control and can be extended to a more general lighting control by combining with global lighting control schemes.
机译:智能照明系统可自动控制照明照度和色温,以实现高质量的生活以及智慧城市中的节能。智能照明控制需要一种实时活动理解系统,该系统需要在变化的照明条件下进行准确的人体位置估计,因为智能照明条件会根据人类活动而变化。本文提出了一种基于人的位置估计的实时智能照明控制系统,该系统基于深度图图像的反透视映射以及根据多个深度相机的移动人的位置,航向和高度估计进行的活动估计。基于估计的到特定活动区域的接近度,到目标照明区域的距离以及人的前进方向的照明控制,提供了一个与活动有关的自动照明环境,并节省了能源。我们实现了几种学习模式,例如学习模式,对话模式和观看电视模式,并将拟议的照明控制系统应用于已知的家具,电子设备和使用多个Kinect深度摄像头的照明位置的客厅照明控制。所提出的模型基于基于局部接近度的照明控制,并且可以通过与全局照明控制方案结合而扩展到更通用的照明控制。

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