Paper ID | IFS-1.1 | ||
Paper Title | SEMI-SUPERVISED FEATURE EMBEDDING FOR DATA SANITIZATION IN REAL-WORLD EVENTS | ||
Authors | Bahram Lavi, Jose Nascimento, Anderson Rocha, University of Campinas, Brazil | ||
Session | IFS-1: Multimedia Forensics 1 | ||
Location | Gather.Town | ||
Session Time: | Tuesday, 08 June, 13:00 - 13:45 | ||
Presentation Time: | Tuesday, 08 June, 13:00 - 13:45 | ||
Presentation | Poster | ||
Topic | Information Forensics and Security: [MMH-OTHS] Forensics & Security Related Applications | ||
IEEE Xplore Open Preview | Click here to view in IEEE Xplore | ||
Abstract | With the rapid growth of data sharing through social media networks, determining relevant data items concerning a particular subject becomes paramount. We address the issue of establishing which images represent an event of interest through a semi-supervised learning technique. The method learns consistent and shared features related to an event (from a small set of examples) to propagate them to an unlabeled set. We investigate the behavior of five image feature representations considering low- and high-level features and their combinations. We evaluate the effectiveness of the feature embedding approach on five collected datasets from real-world events. |