Visual Navigation of Large Image Graphs
2019 IEEE 21st International Workshop on Multimedia Signal Processing (MMSP '19)
TL;DR
We present a graph-based system for visually exploring and navigating millions of images in a web browser. This demo retrieves subsets of images from a similarity graph and displays them as a zoomable, draggable 2D map.
Abstract
It is impossible to inspect or get an overview of image collections with millions of images. Users often start ”exploring” images with a keyword or a similarity search. Both lead to long unstructured lists of result images. In this demo we present a graph-based system for visually exploring and navigating continuously changing sets of millions of images with a web browser. Subsets of images are successively retrieved from a image similarity graph and displayed as a visually sorted 2D image map, which can be zoomed and dragged to explore images from related concepts.
BibTeX
If you use our work in your research, please cite our publication:
@INPROCEEDINGS{8901776,
author={Hezel, Nico and Barthel, Kai Uwe and Schall, Konstantin and Jung, Klaus},
booktitle={2019 IEEE 21st International Workshop on Multimedia Signal Processing (MMSP)},
title={Visual Navigation of Large Image Graphs},
year={2019},
volume={},
number={},
pages={1-1},
keywords={Image retrieval;Graph Navigation},
doi={10.1109/MMSP.2019.8901776}
}