使用智能眼镜在零售商店中实现物理分析

S. Rallapalli, Aishwarya Ganesan, Krishna Chintalapudi, V. Padmanabhan, L. Qiu
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引用次数: 96

摘要

我们考虑在零售商店等室内空间跟踪用户的物理浏览问题。类似于在线浏览,用户选择进入某些网页,停留在他们感兴趣的页面子集上,点击感兴趣的链接而忽略其他,我们可以在物理环境中进行类比,用户可能有目的地走到感兴趣的部分,在那里停留一会儿,凝视特定的项目,然后伸手去看他们想要更仔细地检查的项目。作为我们的第一个贡献,我们设计了一种技术来跟踪物理浏览的每个元素,使用智能眼镜支持的第一人称视觉,以及使用眼镜和智能手机的惯性传感。我们通过使用更便宜的惯性传感器来触发更昂贵的视觉处理来解决关键挑战,包括能源效率。其次,在凝视过程中,我们提出了一种基于测量用户头部方向来识别用户可能关注的物品的方法。最后,不像在网络环境中,每个网页只需点击一下,距离在实体浏览设置中很重要。为了能够跟踪附近的物品,即使在视野之外,我们使用从使用智能眼镜的用户收集的数据来推断产品布局,使用一种称为自动布局的新技术。此外,我们还展示了从一小部分使用智能眼镜的用户中得出的推断如何有助于跟踪许多只使用智能手机的用户的物理浏览。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Enabling physical analytics in retail stores using smart glasses
We consider the problem of tracking physical browsing by users in indoor spaces such as retail stores. Analogous to online browsing, where users choose to go to certain webpages, dwell on a subset of pages of interest to them, and click on links of interest while ignoring others, we can draw parallels in the physical setting, where a user might walk purposefully to a section of interest, dwell there for a while, gaze at specific items, and reach out for the ones that they wish to examine more closely. As our first contribution, we design techniques to track each of these elements of physical browsing using a combination of a first-person vision enabled by smart glasses, and inertial sensing using both the glasses and a smartphone. We address key challenges, including energy efficiency by using the less expensive inertial sensors to trigger the more expensive vision processing. Second, during gazing, we present a method for identifying the item(s) within view that the user is likely to focus on based on measuring the orientation of the user's head. Finally, unlike in the online context, where every webpage is just a click away, proximity is important in the physical browsing setting. To enable the tracking of nearby items, even if outside the field of view, we use data gathered from smart-glasses-enabled users to infer the product layout using a novel technique called AutoLayout. Further, we show how such inferences made from a small population of smart-glasses-enabled users could aid in tracking the physical browsing by the many smartphone-only users.
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