根据上下文信息选择带有智能玻璃的家电

Quan Kong, T. Maekawa, Taiki Miyanishi, Takayuki Suyama
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引用次数: 17

摘要

我们提出了一种使用智能玻璃选择家用电器的方法,该方法有助于控制智能房屋中的联网设备。我们提出的方法是基于图像的设备选择,使智能玻璃用户只需查看即可轻松选择特定的设备。我们的方法的主要特点是,它使用用户的上下文信息(如位置和活动)来实现高精度的电器选择,这些信息是从各种传感器数据中推断出来的,此外还有玻璃捕获的相机图像,因为这些上下文信息与用户想要控制的家用电器在日常生活中有很大的关系。在多核学习框架内,我们通过融合深度学习技术提取的图像特征和非参数贝叶斯技术估计的上下文信息,设计了一种最先进的设备选择方法。我们的实验结果表明,我们的方法是有效的,我们使用的传感器数据是在一个装有许多联网设备的实际房屋中获得的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Selecting home appliances with smart glass based on contextual information
We propose a method for selecting home appliances using a smart glass, which facilitates the control of network-connected appliances in a smart house. Our proposed method is image-based appliance selection and enables smart glass users to easily select a particular appliance by just looking at it. The main feature of our method is that it achieves high precision appliance selection using user contextual information such as position and activity, inferred from various sensor data in addition to camera images captured by the glass because such contextual information is greatly related in the home appliance that a user wants to control in her daily life. We design a state-of-the-art appliance selection method by fusing image features extracted by deep learning techniques and context information estimated by non-parametric Bayesian techniques within a framework of multiple kernel learning. Our experimental results, which use sensor data obtained in an actual house equipped with many network-connected appliances, show the effectiveness of our method.
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