A Novel Bag-of-Visual-Words Approach for Geospatial Object Detection

Date

2011-04-29

Author

Aytekin, Caglar
Alatan, Abdullah Aydın

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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A novel bag-of-visual-words algorithm is presented with two extensions compared to its classical version: exploiting scale information and weighting visual words. The scale information that is already extracted with SIFT detector is included as an additional element to the SIFT key-point descriptor, while the visual words are weighted during histogram assignment proportional to their importance which is measured by the ratio of their occurrences in the object to the occurrences in the background. The algorithm is tested for different geo-spatial object classes and the performance of the classical bag-of-visual-words algorithm is compared against the classical approach. Based on these results, a significant improvement is observed in terms of detection performance.

Subject Keywords

Bag-of-visual-words, Geospatial object recognition, SIFT, Scale information, Weighting visual words

URI

https://hdl.handle.net/11511/48102

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Department of Electrical and Electronics Engineering, Conference / Seminar