Scalable Sketch-Based Image Retrieval Using Color Gradient Features
Abstract
We present a scalable system for sketch-based image retrieval (SBIR), extending the state of the art Gradient Field HoG (GF-HoG) retrieval framework through two technical contributions. First, we extend GF-HoG to enable color-shape retrieval and comprehensively evaluate several early-and late-fusion approaches for integrating the modality of color, considering both the accuracy and speed of sketch retrieval. Second, we propose an efficient inverse-index representation for GF-HoG that delivers scalable search with interactive query times over millions of images. A mobile app demo accompanies this paper (Android).
Cite
Text
Bui and Collomosse. "Scalable Sketch-Based Image Retrieval Using Color Gradient Features." IEEE/CVF International Conference on Computer Vision Workshops, 2015. doi:10.1109/ICCVW.2015.133Markdown
[Bui and Collomosse. "Scalable Sketch-Based Image Retrieval Using Color Gradient Features." IEEE/CVF International Conference on Computer Vision Workshops, 2015.](https://mlanthology.org/iccvw/2015/bui2015iccvw-scalable/) doi:10.1109/ICCVW.2015.133BibTeX
@inproceedings{bui2015iccvw-scalable,
title = {{Scalable Sketch-Based Image Retrieval Using Color Gradient Features}},
author = {Bui, Tu and Collomosse, John P.},
booktitle = {IEEE/CVF International Conference on Computer Vision Workshops},
year = {2015},
pages = {1012-1019},
doi = {10.1109/ICCVW.2015.133},
url = {https://mlanthology.org/iccvw/2015/bui2015iccvw-scalable/}
}