A Retrieval System for Images and Videos based on Aesthetic Assessment of Visuals
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Date
2023-07-18Type
- Conference Paper
ETH Bibliography
yes
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Abstract
Attractive images or videos are the visual backbones of journalism and social media to gain the user's attention. From trailers to teaser images to image galleries, appealing visuals have only grown in importance over the years. However, selecting eye-catching shots from a video or the perfect image from large image collections is a challenging and time-consuming task. We present our tool that can assess image and video content from an aesthetic standpoint. We discovered that it is possible to perform such an assessment by combining expert knowledge with data-driven information. We combine the relevant aesthetic features and machine learning algorithms into an aesthetics retrieval system, which enables users to sort uploaded visuals based on an aesthetic score and interact with additional photographic, cinematic, and person-specific features. Show more
Publication status
publishedExternal links
Book title
SIGIR '23: Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information RetrievalPages / Article No.
Publisher
Association for Computing MachineryEvent
Subject
Multimedia Retrieval; Aesthetics Assessment; Retrieval SystemOrganisational unit
02154 - Media Technology Center (MTC) / Media Technology Center (MTC)
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ETH Bibliography
yes
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