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The availability and use of egocentric data are rapidly increasing due to thegrowing use of wearable cameras. Our aim is to study the effect (positive,neutral or negative) of egocentric images or events on an observer. Givenegocentric photostreams capturing the wearer's days, we propose a method thataims to assign sentiment to events extracted from egocentric photostreams. Suchmoments can be candidates to retrieve according to their possibility ofrepresenting a positive experience for the camera's wearer. The proposedapproach obtained a classification accuracy of 75% on the test set, with adeviation of 8%. Our model makes a step forward opening the door to sentimentrecognition in egocentric photostreams.

Towards Emotion Retrieval in Egocentric PhotoStream