OREGON STATE UNIVERSITY

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Towards recognizing "cool"

TitleTowards recognizing "cool"
Publication TypeConference Paper
Year of Publication2012
AuthorsCurran, W., T. Moore, T. Kulesza, W-K. Wong, S. Todorovic, S. Stumpf, R. White, and M. M. Burnett
Tertiary AuthorsDuarte, C., L. Carriço, J. Jorge, S. Oviatt, and D. Gonçalves
Conference Name2012 ACM international conference on Intelligent User Interfaces - IUI '12
Pagination285-288
Date Published03/2012
PublisherACM Press
Conference LocationLisbon, Portugal
ISBN Number9781450310482
Keywordsclassification, computer vision, human factors, interactive machine learning, learning, user/machine systems
Abstract

Recent computer vision approaches are aimed at richer image interpretations that extend the standard recognition of objects in images (e.g., cars) to also recognize object attributes (e.g., cylindrical, has-stripes, wet). However, the more idiosyncratic and abstract the notion of an object attribute (e.g., cool car), the more challenging the task of attribute recognition. This paper considers whether end users can help vision algorithms recognize highly idiosyncratic attributes, referred to here as subjective attributes. We empirically investigated how end users recognized three subjective attributes of carscool, cute, and classic. Our results suggest the feasibility of vision algorithms recognizing subjective attributes of objects, but an interactive approach beyond standard supervised learning from labeled training examples is needed.

DOI10.1145/2166966.2167019