Automatic segmentation of indoor and outdoor scenes from visual lifelogging

Juan Buhagiar, Nicola Strisciuglio, Nicolai Petkov, George Azzopardi

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

Abstract

Visual Lifelogging is the process of keeping track of one's life through wearable cameras. The focus of this research is to automatically classify images, captured from a wearable camera, into indoor and outdoor scenes. The results of this classification may be used in several applications. For instance, one can quantify the time a person spends outdoors and indoors which may give insights about the psychology of the concerned person. We use transfer learning from two VGG convolutional neural networks (CNN), one that is pre-trained on the ImageNet data set and the other on the Places data set. We investigate two methods of combining features from the two pre-trained CNNs. We evaluate the performance on the new UBRug data set and the benchmark SUN397 data set and achieve accuracy rates of 98.24% and 97.06%, respectively. Features obtained from the ImageNet pretrained CNN turned out to be more effective than those obtained from the Places pre-trained CNN. Fusing the feature vectors obtained from these two CNNs is an effective way to improve the classification. In particular, the performance that we achieve on the SUN397 data set outperforms the state-of-the-art.

Original languageEnglish
Title of host publicationApplications of Intelligent Systems - Proceedings of the 1st International APPIS Conference 2018, APPIS 2018
EditorsNicolai Petkov, Nicola Strisciuglio, Carlos M. Travieso-Gonzalez
PublisherIOS Press
Pages194-202
Number of pages9
ISBN (Electronic)978-1-61499-929-4
ISBN (Print)978-1-61499-928-7
DOIs
Publication statusPublished - 1 Jan 2018
Externally publishedYes
Event1st International Conference on Applications of Intelligent Systems, APPIS 2018 - Las Palmas de Gran Canaria, Spain
Duration: 10 Jan 201812 Jan 2018
Conference number: 1

Publication series

NameFrontiers in Artificial Intelligence and Applications
PublisherIOS Press
Volume310
ISSN (Print)0922-6389

Conference

Conference1st International Conference on Applications of Intelligent Systems, APPIS 2018
Abbreviated titleAPPIS
CountrySpain
CityLas Palmas de Gran Canaria
Period10/01/1812/01/18

Keywords

  • CNN
  • Indoor and Outdoor
  • Scene Classification
  • Transfer Learning

Fingerprint Dive into the research topics of 'Automatic segmentation of indoor and outdoor scenes from visual lifelogging'. Together they form a unique fingerprint.

  • Cite this

    Buhagiar, J., Strisciuglio, N., Petkov, N., & Azzopardi, G. (2018). Automatic segmentation of indoor and outdoor scenes from visual lifelogging. In N. Petkov, N. Strisciuglio, & C. M. Travieso-Gonzalez (Eds.), Applications of Intelligent Systems - Proceedings of the 1st International APPIS Conference 2018, APPIS 2018 (pp. 194-202). (Frontiers in Artificial Intelligence and Applications; Vol. 310). IOS Press. https://doi.org/10.3233/978-1-61499-929-4-194