Where is my Phone ? Personal Object Retrieval from Egocentric Images
  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. 
Cristian Reyes, Eva Mohedano, Kevin McGuinness, Noel E. O'Connor and   Xavier Giro-i-Nieto
cs.IR cs.CV