INCEPTIVE EVENT TIME-SURFACES FOR OBJECT CLASSIFICATION USING NEUROMORPHIC CAMERAS
UNIVERSITY OF DAYTON
R. Wes Baldwin, Mohammed Almatrafi, Jason R. Kaufman, Vijayan Asari, Keigo Hirakawa
ABSTRACT
This paper presents a novel fusion of low-level approaches for dimensionality reduction into an effective approach for high-level objects in neuromorphic camera data called Inceptive Event Time-Surfaces (IETS). IETSs overcome several limitations of conventional time-surfaces by increasing robustness to noise, promoting spatial consistency, and improving the temporal localization of (moving) edges. Combining IETS with transfer learning improves state-of-the-art performance on the challenging problem of object classification utilizing event camera data.
