Demo: Visual Attention for Omnidirectional Images in VR Applications


Understanding visual attention has always been a topic of great interest in different research communities. This is particularly important in omnidirectional images (ODIs) viewed with a head-mounted display (HMD), where only a fraction of the captured scene is displayed at a time, namely viewport.

Here, we share a demo that displays a set of ODIs (provided by the user or using the ones available), while it collects the viewport’s center position at every animation frame for each ODI. The data collected is automatically downloaded at the end of the session.



Croci, Simone; Knorr, Sebastian; Smolic, Aljosa

Saliency-Based Sharpness Mismatch Detection For Stereoscopic Omnidirectional Images Inproceedings

14th European Conference on Visual Media Production, London, UK, 2017.

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Croci, Simone; Knorr, Sebastian; Goldmann, Lutz; Smolic, Aljosa

A Framework for Quality Control in Cinematic VR Based on Voronoi Patches and Saliency Inproceedings

International Conference on 3D Immersion, Brussels, Belgium, 2017.

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Monroy, Rafael; Lutz, Sebastian; Chalasani, Tejo; Smolic, Aljosa

SalNet360: Saliency Maps for omni-directional images with CNN Unpublished


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Abreu, Ana De; Ozcinar, Cagri; Smolic, Aljosa

Look around you: saliency maps for omnidirectional images in VR applictions Inproceedings

9th International Conference on Quality of Multimedia Experience (QoMEX), 2017.

Abstract | Links | BibTeX