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Title: Ranking regions of visual saliency in RGB-D content
Authors: Seychell, Dylan
Debono, Carl James
Keywords: Image segmentation
Virtual reality
Human-computer interaction -- Case studies
Issue Date: 2018
Publisher: IEEE
Citation: Seychell, D., & Debono, C. J. (2018). Ranking regions of visual saliency in RGB-D content. 2018 International Conference on 3D Immersion (IC3D), Brussels.
Abstract: Effective immersion takes place when the user can relate to the 3D environment presented and interact with key objects. Efficiently predicting which objects in a scene are in the user's attention, without using additional hardware, such as eye tracking solutions, provides an opportunity for creating more immersive scenes in real time and at lower costs. This is nonetheless algorithmically challenging. In this paper, we are proposing a technique that efficiently and effectively identifies the most salient objects in a scene. We show how it accurately matches user selection within 0.04s and is over 95% faster than other saliency algorithms while also providing a ranking of the most salient segments in a scene.
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