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Place Recognition Using Multiple Wearable Cameras

机译:使用多个可穿戴式摄像机进行位置识别

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摘要

Recognizing a user's location is the most challenging problem for providing intelligent location-based services. In this paper, we presented a realtime camera-based system for the place recognition problem. This system takes streams of scene images of a learned environment from user-worn cameras and produces the class label of the current place as an output. Multiple cameras are used to collect multi-directional scene images because utilizing multiple images yields better and robust recognition than a single image. For more robust recognition, we utilized spatial relationships between the places. In addition that, a temporal reasoning is incorporated with a Markov model to reflect typical staying time at each place. Recognition experiments, which were conducted in a real environment in a university campus, showed that the proposed method yields a very promising result.
机译:提供智能的基于位置的服务时,识别用户的位置是最具挑战性的问题。在本文中,我们提出了一个基于实时相机的系统来解决位置识别问题。该系统从用户佩戴的相机获取学习环境的场景图像流,并生成当前位置的类别标签作为输出。使用多个摄像机来收集多方向的场景图像,因为与使用单个图像相比,利用多个图像可产生更好且更可靠的识别。为了获得更可靠的识别,我们利用了地点之间的空间关系。此外,时间推理与马尔可夫模型相结合以反映每个位置的典型停留时间。在大学校园的真实环境中进行的识别实验表明,该方法产生了非常有希望的结果。

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