  With the rapid increase of users of wearable cameras in recent years and of
the amount of data they produce, there is a strong need for automatic retrieval
and summarization techniques. This work addresses the problem of automatically
summarizing egocentric photo streams captured through a wearable camera by
taking an image retrieval perspective. After removing non-informative images by
a new CNN-based filter, images are ranked by relevance to ensure semantic
diversity and finally re-ranked by a novelty criterion to reduce redundancy. To
assess the results, a new evaluation metric is proposed which takes into
account the non-uniqueness of the solution. Experimental results applied on a
database of 7,110 images from 6 different subjects and evaluated by experts
gave 95.74% of experts satisfaction and a Mean Opinion Score of 4.57 out of
5.0. Source code is available at
https://github.com/imatge-upc/egocentric-2017-lta
