Neuromorphic Vision-based Motion Segmentation with Graph Transformer Neural Network

arXiv:2404.10940v1 Announce Type: new
Abstract: Moving object segmentation is critical to interpret scene dynamics for robotic navigation systems in challenging environments. Neuromorphic vision sensors are tailored for motion perception due to their asynchronous nature, high temporal resolution, and reduced power consumption. However, their unconventional output requires novel perception paradigms to leverage their spatially sparse and temporally dense nature. In this work, we propose a novel event-based motion segmentation algorithm using a Graph Transformer Neural Network, dubbed GTNN. Our proposed algorithm …

abstract arxiv asynchronous consumption cs.cv dynamics environments graph however moving nature navigation network neural network neuromorphic novel object perception power power consumption resolution robotic segmentation sensors systems temporal transformer type vision