V-RSIR: A WEB-BASED TOOL AND BENCHMARK DATASET FOR REMOTE SENSING IMAGE RETRIEVAL
Benchmark datasets play an important role in evaluating remote sensing image retrieval methods. Current benchmark datasets are mostly collected through the Google Map API or other desktop tools. However, the Google Map API requires the users to have programming skills and other collection tools are...
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2019-06-01
|
| Series: | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| Online Access: | https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-2-W13/1545/2019/isprs-archives-XLII-2-W13-1545-2019.pdf |
| Summary: | Benchmark datasets play an important role in evaluating remote sensing image retrieval methods. Current benchmark datasets are mostly collected through the Google Map API or other desktop tools. However, the Google Map API requires the users to have programming skills and other collection tools are not publicly available, which may hinder the development of new benchmark datasets. This paper develops an open access web-based tool V-RSIR to help users generating new benchmark datasets with volunteers for remote sensing image retrieval. Using this tool, a new benchmark dataset V-RSIR that contains 38 classes with at least 1500 images per class is created by 32 volunteers. A handcrafted low-level feature method and a deep learning high-level feature method are used to test the dataset. The evaluation results are consistent with our perception. This shows that the tool can help users effectively creating benchmark datasets for RSIR. |
|---|---|
| ISSN: | 1682-1750 2194-9034 |