Automatic Name-Face Alignment to Enable Cross-Media News Retrieval
Proceedings of the Twenty-Third International Joint Conference on Artificial Intelligence. Pages 2768-2774.
Abstract
A new algorithm is developed in this paper to support automatic name-face alignment for achieving more accurate cross-media news retrieval. We focus on extracting valuable information from large amounts of news images and their captions, where multi-level image-caption pairs are constructed for characterizing both significant names with higher salience and their cohesion with human faces extracted from news images. To remedy the issue of lacking enough related information for rare name, Web mining is introduced to acquire the extra multimodal information. We also emphasize on an optimization mechanism by our Improved Self-Adaptive Simulated Annealing Genetic Algorithm to verify the feasibility of alignment combinations. Our experiments have obtained very positive results.
@inproceedings{ijcai2013p407,
title = {Automatic Name-Face Alignment to Enable Cross-Media News Retrieval},
author = {Zhang, Yuejie and Wu, Wei and Li, Yang and Jin, Cheng and Xue, Xiangyang and Fan, Jianping},
booktitle = {Proceedings of the Twenty-Third International Joint Conference on
Artificial Intelligence, {IJCAI-13}},
publisher = {AAAI Press / International Joint Conferences on Artificial Intelligence},
editor = {Francesca Rossi},
pages = {2768--2774},
year = {2013},
month = {8},
url = {https://ijcai.org/proceedings/2013/407},
}
TY - CPAPER TI - Automatic Name-Face Alignment to Enable Cross-Media News Retrieval AU - Zhang, Yuejie AU - Wu, Wei AU - Li, Yang AU - Jin, Cheng AU - Xue, Xiangyang AU - Fan, Jianping T2 - Proceedings of the Twenty-Third International Joint Conference on Artificial Intelligence, IJCAI-13 PB - AAAI Press / International Joint Conferences on Artificial Intelligence PY - 2013 SP - 2768 EP - 2774 UR - https://ijcai.org/proceedings/2013/407 ER -Copied
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