BibTex
@inproceedings{Gan:2019:10.20380/GI2019.06,
author = {Gan, Yuan and Zhang, Yan and Sun, Zhengxing and Zhang, Hao},
title = {Qualitative Organization of Photo Collections via Quartet Analysis and Active Learning},
booktitle = {Proceedings of Graphics Interface 2019},
series = {GI 2019},
year = {2019},
issn = {0713-5424},
isbn = {978-0-9947868-4-5},
location = {Kingston, Ontario},
numpages = {8},
doi = {10.20380/GI2019.06},
publisher = {Canadian Information Processing Society},
}
Abstract
We introduce the use of qualitative analysis and active learning to photo album construction. Given a heterogeneous collection of photos, we organize them into a hierarchical categorization tree (C-tree) based on qualitative analysis using quartets instead of relying on conventional, quantitative image similarity metrics. The main motivation is that in a heterogeneous collection, quantitative distances may become unreliable between dissimilar data and there is unlikely a single metric that is well applicable to all data. Our qualitative analysis utilizes multiple distance measures and applies them where reliable comparisons are possible. Then from the C-tree, we develop an active learning scheme for fine-grained photo scene classification, allowing the selection of representative photos for layout construction which better reflects user intent. Finally, the selected photos are laid out in a comic-like arrangement based on a style template library and layout optimization. Experiments demonstrate that our method is efficient, user-centered, and produces photo albums that are more preferable in comparison with previous approaches.