用于位置识别的全景到全景匹配

Proceedings of the 2017 ACM on International Conference on Multimedia Retrieval Pub Date : 2017-04-21 DOI:10.1145/3078971.3079033

Ahmet Iscen, Giorgos Tolias, Yannis Avrithis, T. Furon, Ondřej Chum

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引用次数: 25

摘要

位置识别通常被视为街景图像的视觉实例检索。数据集项目和查询是全景视图，即在单个位置拍摄的图像组。这项工作引入了一种新的全景到全景匹配过程，要么通过将单个图像的特征聚合在一组中，要么通过明确地构建一个更大的全景。在任何一种情况下，都会使用多个视图作为查询。我们在只有四个查询视图的标准基准上达到了近乎完美的位置识别。

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Panorama to Panorama Matching for Location Recognition

Location recognition is commonly treated as visual instance retrieval on "street view" imagery. The dataset items and queries are panoramic views, i.e. groups of images taken at a single location. This work introduces a novel panorama-to-panorama matching process, either by aggregating features of individual images in a group or by explicitly constructing a larger panorama. In either case, multiple views are used as queries. We reach near perfect location recognition on a standard benchmark with only four query views.

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Proceedings of the 2017 ACM on International Conference on Multimedia Retrieval

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