Fuzzy Fusion for Two-stream Action Recognition

Author(s)

Sousa e Santos, Anderson Carlos ; Maia, Helena de Almeida ; Roberto e Souza, Marcos ; Vieira, Marcelo Bernardes ; Pedrini, Helio ; Farinella, GM ; Radeva, P ; Braz, J

• Document type: Journal article
• Source: VISAPP: PROCEEDINGS OF THE 15TH INTERNATIONAL JOINT CONFERENCE ON COMPUTER VISION, IMAGING AND COMPUTER GRAPHICS THEORY AND APPLICATIONS, VOL 4: VISAPP; v. N/A, p. 7-pg., 2020-01-01.

Abstract

There are several aspects that may help in the characterization of an action being performed in a video, such as scene appearance and estimated movement of the involved objects. Many works in the literature combine different aspects to recognize the actions, which has shown to be superior than individual results. Just as important as the definition of representative and complementary aspects is the choice of good combination methods that exploit the strengths of each aspect. In this work, we propose a novel fusion strategy based on two fuzzy integral methods. This strategy is capable of generalizing other common operators, besides it allows more combinations to be evaluated by having a distinct impact in sets linearly dependent. Our experiments show that the fuzzy fusion outperforms the most commonly-used weighted average on the challenging UCF101 and HMDB51 datasets. (AU)

• FAPESP's process: 17/12646-3 - Déjà vu: feature-space-time coherence from heterogeneous data for media integrity analytics and interpretation of events
• Grantee: Anderson de Rezende Rocha
• Support Opportunities: Research Projects - Thematic Grants
• FAPESP's process: 17/09160-1 - Human Action Recognition in Videos
• Grantee: Helena de Almeida Maia
• Support Opportunities: Scholarships in Brazil - Doctorate