7 papers
Neuromorphic Object Detection: An In-Depth Study and Future Directions
Jianing Li, Dianze Li, Arren Glover +5
Conventional frame-based cameras face significant challenges in detecting objects under high-speed motion blur or in low-light environments. Neuromorphic cameras provide asynchrono…
Event-based Motion & Appearance Fusion for 6D Object Pose Tracking
Zhichao Li, Chiara Bartolozzi, Lorenzo Natale +1
Object pose tracking is a fundamental and essential task for robotics to perform tasks in the home and industrial settings. The most commonly used sensors to do so are RGB-D camera…
GraphEnet: Event-driven Human Pose Estimation with a Graph Neural Network
Gaurvi Goyal, Pham Cong Thuong, Arren Glover +2
Human Pose Estimation is a crucial module in human-machine interaction applications and, especially since the rise in deep learning technology, robust methods are available to cons…
Lattice-allocated Real-time Line Segment Feature Detection and Tracking Using Only an Event-based Camera
Mikihiro Ikura, Arren Glover, Masayoshi Mizuno +1
Line segment extraction is effective for capturing geometric features of human-made environments. Event-based cameras, which asynchronously respond to contrast changes along edges,…
6-DoF Object Tracking with Event-based Optical Flow and Frames
Zhichao Li, Arren Glover, Chiara Bartolozzi +1
Tracking the position and orientation of objects in space (i.e., in 6-DoF) in real time is a fundamental problem in robotics for environment interaction. It becomes more challengin…
IMA-Catcher: An IMpact-Aware Nonprehensile Catching Framework based on Combined Optimization and Learning
Francesco Tassi, Jianzhuang Zhao, Gustavo J. G. Lahr +5
Robotic catching of flying objects typically generates high impact forces that might lead to task failure and potential hardware damages. This is accentuated when the object mass t…