dc.contributor.author | Sidorov, Oleksii | |
dc.contributor.author | Pedersen, Marius | |
dc.contributor.author | Shekhar, Sumit | |
dc.contributor.author | Wook Kim, Nam | |
dc.date.accessioned | 2021-02-24T12:52:26Z | |
dc.date.available | 2021-02-24T12:52:26Z | |
dc.date.created | 2020-06-08T11:32:46Z | |
dc.date.issued | 2020 | |
dc.identifier.isbn | 978-1-4503-6819-3 | |
dc.identifier.uri | https://hdl.handle.net/11250/2730123 | |
dc.description.abstract | In this work, we address the problem of measuring and predicting temporal video saliency - a metric which defines the importance of a video frame for human attention. Unlike the conventional spatial saliency which defines the location of the salient regions within a frame (as it is done for still images), temporal saliency considers importance of a frame as a whole and may not exist apart from context. The proposed interface is an interactive cursor-based algorithm for collecting experimental data about temporal saliency. We collect the first human responses and perform their analysis. As a result, we show that qualitatively, the produced scores have very explicit meaning of the semantic changes in a frame, while quantitatively being highly correlated between all the observers. | en_US |
dc.language.iso | eng | en_US |
dc.publisher | ACM | en_US |
dc.relation.ispartof | CHI EA '20: Extended Abstracts of the 2020 CHI Conference on Human Factors in Computing Systems | |
dc.title | Are All the Frames Equally Important? | en_US |
dc.type | Chapter | en_US |
dc.description.version | publishedVersion | en_US |
dc.identifier.doi | 10.1145/3334480.3382980 | |
dc.identifier.cristin | 1814290 | |
dc.description.localcode | This article will not be available due to copyright restrictions (c) 2020 by ACM | en_US |
cristin.ispublished | true | |
cristin.fulltext | original | |
cristin.qualitycode | 1 | |