.

Personalized social image organization, visualization, and querying tool using low- and high-level features

LAUR Repository

Show simple item record

dc.contributor.author Tekli, Joe
dc.contributor.author Ayoub, Issa
dc.contributor.author Codoumi, Karl J.
dc.date.accessioned 2018-02-08T13:00:25Z
dc.date.available 2018-02-08T13:00:25Z
dc.date.copyright 2016 en_US
dc.date.issued 2018-02-08
dc.identifier.isbn 978-1-5090-3593-9 en_US
dc.identifier.uri http://hdl.handle.net/10725/7057
dc.description.abstract The purpose of this study is to create a software system to facilitate the organization of and searching for social images acquired from social sites on the Web (such as Facebook or Flikr), taking into account the images' features as well as user preferences. To achieve our goal, we design a solution based on image clustering, grouping together images sharing similar semantic and visual features, to simplify their organization and querying. This requires low-level and high-level image feature extraction and processing, where: low-level features represent color, texture, and shape image descriptors, whereas high-level features consist of textual descriptors extracted from image annotations and surrounding texts. Our system consists of modular components for: i) feature extraction and representation (low-level and high-level), ii) partitional image clustering (initial clustering phase executed when the user first connects to the system), iii) incremental clustering (updating clusters produces in the previous phase by processing newly published images), iv) fast image querying (using features of cluster representatives), and v) personalized images/search results visualization (using various user-chosen cluster display techniques). Preliminary experiments highlight the efficiency and practicality of our tool. en_US
dc.language.iso en en_US
dc.publisher IEEE en_US
dc.title Personalized social image organization, visualization, and querying tool using low- and high-level features en_US
dc.type Conference Paper / Proceeding en_US
dc.author.school SOE en_US
dc.author.idnumber 201306321 en_US
dc.author.department Electrical And Computer Engineering en_US
dc.description.embargo N/A en_US
dc.keywords Image color analysis en_US
dc.keywords Feature extraction en_US
dc.keywords Organizations en_US
dc.keywords Shape en_US
dc.keywords Histograms en_US
dc.keywords Image edge detection en_US
dc.keywords Visualization en_US
dc.identifier.doi http://dx.doi.org/10.1109/CSE-EUC-DCABES.2016.199 en_US
dc.identifier.ctation Ayoub, I., Codoumi, K. J., & Tekli, J. (2016, August). Personalized Social Image Organization, Visualization, and Querying Tool Using Low-and High-Level Features. In Computational Science and Engineering (CSE) and IEEE Intl Conference on Embedded and Ubiquitous Computing (EUC) and 15th Intl Symposium on Distributed Computing and Applications for Business Engineering (DCABES), 2016 IEEE Intl Conference on (pp. 287-294). IEEE. en_US
dc.author.email joe.tekli@lau.edu.lb en_US
dc.conference.date 24-26 Aug. 2016 en_US
dc.conference.place Paris, France en_US
dc.conference.title 2016 IEEE Intl Conference on Computational Science and Engineering (CSE) and IEEE Intl Conference on Embedded and Ubiquitous Computing (EUC) and 15th Intl Symposium on Distributed Computing and Applications for Business Engineering (DCABES) en_US
dc.identifier.tou http://libraries.lau.edu.lb/research/laur/terms-of-use/articles.php en_US
dc.identifier.url http://ieeexplore.ieee.org/abstract/document/7982261/ en_US
dc.publication.date 2016 en_US
dc.author.affiliation Lebanese American University en_US


Files in this item

Files Size Format View

There are no files associated with this item.

This item appears in the following Collection(s)

Show simple item record

Search LAUR


Advanced Search

Browse

My Account