@inproceedings{6040d954d7e34a8497a84384daa897cf,
title = "Studying object naming with online photos and caption",
abstract = "We explore what names people use to describe visual concepts and why these names are chosen. Choosing object names has been a topic of interest in cognitive psychology, but a systematic, data-driven approach for naming at the scale of thousands of objects does not yet exist. First, we -nd that visual context has interpretable e-ects on visual naming, by analysing the MSCOCO dataset that has manually annotated objects and captions containing the natural language names for the object. We show that taking into account other objects as context helps improve the prediction of object names. We then analyse the naming patterns on a large dataset from Flickr, using automatically detected concepts. Preliminary results indicate that naming patterns can be identi-ed on a large scale, but contrary to the conventional wisdom in cognitive psychology, are not dominated by genus for animals. We further validate the automatic method with a pilot Amazon Mechanical Turk naming experiment, and explore the impact of automatic concept detectors with t-SNE visualizations.",
keywords = "Learning, Multimedia, Naming",
author = "Alexander Mathews and Lexing Xie and Xuming He",
note = "Publisher Copyright: {\textcopyright}10.1145/2814815.2814817.; Workshop on Community-Organized Multimodal Mining: Opportunities for Novel Solutions, MMCommons 2015 ; Conference date: 30-10-2015",
year = "2015",
month = oct,
day = "30",
doi = "10.1145/2814815.2814817",
language = "English",
series = "MMCommons 2015 - Proceedings of the 2015 Workshop on Community-Organized Multimodal Mining: Opportunities for Novel Solutions, co-located with ACM MM 2015",
publisher = "Association for Computing Machinery (ACM)",
pages = "31--36",
booktitle = "MMCommons 2015 - Proceedings of the 2015 Workshop on Community-Organized Multimodal Mining",
address = "United States",
}