Cozi

Carlier, Aurélie; Shafiei, Arash; Badie, Julien; Bensiali, Salim; Ooi, Wei Tsang

doi:10.1145/2072298.2072480

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2023

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“…Zooming interactions [13] consists in giving the observer an interactive zooming tool, and treating the zoomupon areas as areas of interest, from which visual attention heatmaps can be drawn. However, this methods is more suited to multi-scale content.…”

Section: Introductionmentioning

confidence: 99%

Could the BubbleView Metaphor be used to Infer Visual Attention on 3D Graphical Content?

Bruckert

Abid

Silva

et al. 2023

ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

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Understanding the deployment of human gaze on 3D graphical objects is of critical importance in order to propose rich and complex 3D environments without strong latency nor rendering constraints. However, the data needed to study this gaze deployment can be costly and difficult to obtain, especially in the context of the Covid-19 pandemic where in-lab experiments are strongly discouraged. In order to alleviate these issues, we propose to use the BubbleView metaphor as a way of crowdsourcing visual attention data on 3D graphical content. In this paper, we question the adequacy of this method to provide a reliable proxy for visual attention in the context of 3D graphical objects. Moreover, we show that data obtained in this manner can be used to train visual saliency models, with only a slight tradeoff in performances compared to the use of ground-truth eye-tracking data.

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Section: Introductionmentioning

confidence: 99%