Inceptive Event Time-Surfaces for Object Classification Using Neuromorphic Cameras
| Autor: | Vijayan K. Asari, Jason R. Kaufman, R. Wes Baldwin, Keigo Hirakawa, Mohammed Almatrafi |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Event (computing)
business.industry Computer science Dimensionality reduction 020208 electrical & electronic engineering 02 engineering and technology Object (computer science) Neuromorphic engineering Robustness (computer science) 0202 electrical engineering electronic engineering information engineering Spatial consistency 020201 artificial intelligence & image processing Computer vision Artificial intelligence Noise (video) Transfer of learning business |
| Zdroj: | Lecture Notes in Computer Science ISBN: 9783030272715 ICIAR (2) |
| DOI: | 10.1007/978-3-030-27272-2_35 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|