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The impact of temporal regularisation in egocentric saliency prediction

Panagiotis, Linardos, Mohedano, Eva, Cherto, Monica, Gurrin, Cathal orcid logoORCID: 0000-0003-2903-3968 and Giro-i-Nieto, Xavier (2018) The impact of temporal regularisation in egocentric saliency prediction. In: The Third International Workshop on Egocentric Perception, Interaction and Computing (EPIC@ECCV18), 9 Sept 2018, Munich, Germany.

Abstract
This work explores how temporal regularization in egocentric videos may have a positive or negative impact in saliency prediction depending on the viewer behavior. Our study is based on the new EgoMon dataset, which consists of seven videos recorded by three subjects in both free-viewing and task-driven set ups. We predict a frame-based saliency prediction over the frames of each video clip, as well as a temporally regularized version based on deep neural networks. Our results indicate that the NSS saliency metric improves during task-driven activities, but that it clearly drops during free-viewing. Encouraged by the good results in task-driven activities, we also computed and publish the saliency maps for the EPIC Kitchens dataset.
Metadata
Item Type:Conference or Workshop Item (Poster)
Event Type:Workshop
Refereed:Yes
Subjects:Computer Science > Artificial intelligence
Computer Science > Digital video
Computer Science > Lifelog
DCU Faculties and Centres:DCU Faculties and Schools > Faculty of Engineering and Computing > School of Electronic Engineering
Research Institutes and Centres > INSIGHT Centre for Data Analytics
Copyright Information:© The Authors
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
Funders:SFI/12/RC/2289
ID Code:22565
Deposited On:22 Oct 2018 10:53 by Eva Mohedano Robles . Last Modified 22 Oct 2018 10:53
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