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Communication Dans Un Congrès Année : 2018

How Old Do You Look? Inferring Your Age From Your Gaze

Résumé

The visual exploration of a scene, represented by a visual scanpath, depends on a number of factors. Among them, the age of the observer plays a significant role. For instance, young kids are making shorter saccades and longer fixations than adults. In the light of these observations, we propose a new method for inferring the age of the observer from its scanpath. The proposed method is based on a 1D CNN network which is trained by real eye tracking data collected on five age groups. In order to boost the performance, the training dataset is augmented by predicting a high number of scan-paths thanks to the use of an age-dependent computational saccadic model. The proposed method brings a new momentum in this field not only by significantly outperforming existing method but also by being robust to noise and data erasure.
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Dates et versions

hal-01951396 , version 1 (11-12-2018)

Identifiants

  • HAL Id : hal-01951396 , version 1

Citer

Tianyi Zhang, Olivier Le Meur. How Old Do You Look? Inferring Your Age From Your Gaze. International Conference on Image Processing, Oct 2018, Athènes, Greece. ⟨hal-01951396⟩
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