This paper analyzes location recognition by using local features and a simple nearest neighbor approach; after determining the location of each input local feature by nearest neighbor, the final recognition result of the entire input image is determined by voting. Specifically, if the input image is gets N local features, N location candidates are determined by the nearest neighbor (or k-nearest neighbor) from stored scenery images at known locations, and then the most major location is selected as the final location recognition result. Image block and SURF ware employed and examined as local features.
|Translated title of the contribution||Instance-Based Localization Using Local Features|
|Number of pages||6|
|Journal||IEICE technical report|
|Publication status||Published - Feb 11 2010|