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Geo-Location Estimation of Flickr Images: Social Web Based Enrichment

机译:Flickr图像的地理位置估计:基于社交网络的充实

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Estimating the geographic location of images is a task which has received a lot of attention in recent years. Large numbers of items uploaded to Flickr do not contain GPS-based latitude/longitude coordinates, although it would be beneficial to obtain such geographic information for a wide variety of potential applications such as travelogues and visual place descriptions. While most works in this area consider an image's textual meta-data to estimate its geo-location, we consider an additional textual dimension: the image owner's traces on the social Web, in particular on the micro-blogging platform Twitter. We investigate the following question: does enriching an image's available textual meta-data with a user's tweets improve the accuracy of the geographic location estimation process? The results show that this is indeed the case; in an oracle setting, the median error in kilometres decreases by 87%, in the best automatic approach the median error decreases by 56%.
机译:估计图像的地理位置是一项近年来受到广泛关注的任务。上载到Flickr的大量项目不包含基于GPS的纬度/经度坐标,尽管对于许多潜在的应用程序(例如旅行记录和视觉位置描述)获取此类地理信息将是有益的。虽然该领域的大多数作品都考虑图像的文本元数据来估计其地理位置,但我们考虑了另一个文本维度:图像所有者在社交网站上的踪迹,特别是在微博客平台Twitter上。我们研究了以下问题:用用户的推文丰富图像的可用文本元数据是否会提高地理位置估计过程的准确性?结果表明确实如此。在Oracle环境中,以公里为单位的中位误差减少了87%,在最佳自动方法中,中位误差减少了56%。

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