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CROWD-PAN-360: Crowdsourcing Based Context-Aware Panoramic Map Generation for Smartphone Users

机译:CROWD-PAN-360:为智能手机用户基于众包的上下文感知全景地图生成

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Recent advances in smartphones and location-aware services necessitate identifying logical locations of users, in terms of their surroundings, instead of raw location coordinates. In this paper, we have proposed (), a novel smartphone-based system to generate 360-degree panoramic map of a querying user for his unfamiliar surrounding using crowd-sourced images. The objects (logical locations) appearing in the images are identified using manually or automatically generated tags. The system is context-aware and it intelligently associates user location coordinates with several smartphone contexts, like acceleration and orientation. can significantly reduce GPS positional errors for even cheap low-end smartphones and can identify the user surroundings very efficiently. We extensively tested the system in both indoor and outdoor environments of IIT Roorkee campus using Android smartphones over a dataset of more than 6,000 crowd-sourced images of nearly 70 objects (departments, hostels, cafeteria, etc.) and generates the panoramic map with an average accuracy of 92.2 percent.
机译:智能手机和位置感知服务的最新发展需要根据用户的周围环境而不是原始位置坐标来识别用户的逻辑位置。在本文中,我们提出了(),这是一种新颖的基于智能手机的系统,可以使用众包图像生成查询用户的360度全景图,以了解其陌生的周围环境。使用手动或自动生成的标签识别出现在图像中的对象(逻辑位置)。该系统具有上下文感知功能,并且可以智能地将用户位置坐标与多个智能手机上下文(如加速度和方向)相关联。甚至可以为廉价的低端智能手机显着减少GPS定位误差,并且可以非常有效地识别用户周围环境。我们使用Android智能手机在IIT Roorkee校园的室内和室外环境中对该系统进行了广泛的测试,该数据集中包含近70个对象(部门,旅馆,自助餐厅等)的6,000多幅众包图像,并生成了带有平均准确度为92.2%。

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