# All the people around me: face discovery in egocentric photo-streams

arXiv: https://arxiv.org/abs/1703.01790 · HTML: https://mlsanity.com/paper/1703.01790/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 6 Mar 2017.

## Built on by (most cited first, 1 of 1)

- [Interaction-GCN: A Graph Convolutional Network based framework for social interaction recognition in egocentric videos](https://mlsanity.com/paper/2104.14007/) (2021)

## Abstract (arXiv)

Given an unconstrained stream of images captured by a wearable photo-camera (2fpm), we propose an unsupervised bottom-up approach for automatic clustering appearing faces into the individual identities present in these data. The problem is challenging since images are acquired under real world conditions; hence the visible appearance of the people in the images undergoes intensive variations. Our proposed pipeline consists of first arranging the photo-stream into events, later, localizing the appearance of multiple people in them, and finally, grouping various appearances of the same person across different events. Experimental results performed on a dataset acquired by wearing a photo-camera during one month, demonstrate the effectiveness of the proposed approach for the considered purpose.