. EgoMemNet: Visual Memorability Adaptation to Egocentric Images. Las Vegas, NV, USA: 4th Workshop on Egocentric (First-Person) Vision, CVPR 2016; 2016 . 
(265.4 KB)
(265.4 KB) Abstract
This work explores the adaptation of visual memorability prediction for photos intentionally captured by handheld cameras, to images passively captured from an egocentric point of view by wearable cameras. The estimation of a visual memorability score for an egocentric images is a valuable cue when filtering among the large amount of photos generated by wearable cameras. For this purpose, a new annotation tool and annotated dataset are presented, used to fine-tune a pre-trained convolutional neural network.
Extended abstract presented as poster in the 4th Workshop on Egocentric (First-Person) Vision, CVPR 2016.
