This work presents a retrieval pipeline and evaluation scheme for the problem of finding the last appearance of personal objects in a large dataset of images captured from a wearable camera. Each personal object is modelled by a small set of images that define a query for a visual search engine.The retrieved results are reranked considering the temporal timestamps of the images to increase the relevance of the later detections. Finally, a temporal interleaving of the results is introduced for robustness against false detections. The Mean Reciprocal Rank is proposed as a metric to evaluate this problem. This application could help into developing personal assistants capable of helping users when they do not remember where they left their personal belongings.
@article{arxiv.1608.08139,
title = {Where is my Phone ? Personal Object Retrieval from Egocentric Images},
author = {Cristian Reyes and Eva Mohedano and Kevin McGuinness and Noel E. O'Connor and Xavier Giro-i-Nieto},
journal= {arXiv preprint arXiv:1608.08139},
year = {2017}
}
Comments
Lifelogging Tools and Applications Workshop (LTA'16) at ACM Multimedia 2016