%0 Conference Proceedings
%T LEMoRe: A Lifelog Engine for Moments Retrieval at the NTCIR-Lifelog LSAT Task
%A G. de Oliveira
%A A. Cartas
%A Marc Bolaños
%A Mariella Dimiccoli
%A Xavier Giro
%A Petia Radeva
%B 12th NTCIR Conference on Evaluation of Information Access Technologies
%D 2016
%F G. de Oliveira2016
%O MILAB;
%O exported from refbase (http://refbase.cvc.uab.es/show.php?record=2789), last updated on Mon, 03 Jun 2024 08:55:58 +0200
%X Semantic image retrieval from large amounts of egocentric visual data requires to leverage powerful techniques for filling in the semantic gap. This paper introduces LEMoRe, a Lifelog Engine for Moments Retrieval, developed in the context of the Lifelog Semantic Access Task (LSAT) of the the NTCIR-12 challenge and discusses its performance variation on different trials. LEMoRe integrates classical image descriptors with high-level semantic concepts extracted by Convolutional Neural Networks (CNN), powered by a graphic user interface that uses natural language processing. Although this is just a first attempt towards interactive image retrieval from large egocentric datasets and there is a large room for improvement of the system components and the user interface, the structure of the system itself and the way the single components cooperate are very promising.
%U http://refbase.cvc.uab.es/files/DCB2016.pdf