Sentiment recognition in egocentric photostreams

Estefania Talavera*, Nicola Strisciuglio, Nicolai Petkov, Petia Radeva

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

6 Citations (Scopus)

Abstract

Lifelogging is a process of collecting rich source of information about daily life of people. In this paper, we introduce the problem of sentiment analysis in egocentric events focusing on the moments that compose the images recalling positive, neutral or negative feelings to the observer. We propose a method for the classification of the sentiments in egocentric pictures based on global and semantic image features extracted by Convolutional Neural Networks. We carried out experiments on an egocentric dataset, which we organized in 3 classes on the basis of the sentiment that is recalled to the user (positive, negative or neutral).

Original languageEnglish
Title of host publicationPattern Recognition and Image Analysis
Subtitle of host publication8th Iberian Conference, IbPRIA 2017, Faro, Portugal, June 20-23, 2017, Proceedings
EditorsLuís A. Alexandre, José Salvador Sánchez, João M.F. Rodrigues
Place of PublicationCham
PublisherSpringer
Pages471-479
Number of pages9
ISBN (Electronic)978-3-319-58838-4
ISBN (Print)978-3-319-58837-7
DOIs
Publication statusPublished - 1 Jan 2017
Externally publishedYes
Event8th Iberian Conference on Pattern Recognition and Image Analysis, IbPRIA 2017 - Faro, Portugal
Duration: 20 Jun 201723 Jun 2017
Conference number: 8

Publication series

NameLecture Notes in Computer Science
PublisherSpringer
Volume10255
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349
NameImage Processing, Computer Vision, Pattern Recognition, and Graphics
PublisherSpringer

Conference

Conference8th Iberian Conference on Pattern Recognition and Image Analysis, IbPRIA 2017
Abbreviated titleIbPRIA
CountryPortugal
CityFaro
Period20/06/1723/06/17

Keywords

  • Egocentric photos
  • Lifelogging
  • Sentiment image analysis

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