Inceptive Event Time-Surfaces for Object Classification Using Neuromorphic Cameras
- Resource Type
- Working Paper
- Authors
- Baldwin, R Wes; Almatrafi, Mohammed; Kaufman, Jason R; Asari, Vijayan; Hirakawa, Keigo
- Source
- Image Analysis and Recognition. ICIAR 2019. Lecture Notes in Computer Science, vol 11663. Springer, Cham
- Subject
- Computer Science - Neural and Evolutionary Computing
Computer Science - Computer Vision and Pattern Recognition
Electrical Engineering and Systems Science - Image and Video Processing
- Language
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.