Paper Info
Title
Data-Set For Event-Based Optical Flow Evaluation In Robotics Applications
Abstract
Event-Based cameras (also known as Dynamic Vision Sensors "DVS") have been used extensively in robotics during the last ten years and have proved the ability to solve many problems encountered in this domain. Their technology is very different from conventional cameras which requires rethinking the existing paradigms and reviewing all the classical image processing and computer vision algorithms. We show in this paper how Event-Based cameras are naturally adapted to estimate on the fly scene gradients and hence the visual flow. Our work starts with a complete study of existing event-based optical flow algorithms that are suitable to be integrated into real-time robotics applications. Then, we provide a data-set that includes different scenarios along with a set of visual flow ground-truth. Finally, we propose an evaluation of existing event-based visual flow algorithms using the proposed ground truth data-set.
Year
DOI
Venue
2021
10.5220/0010320304800489
VISAPP: PROCEEDINGS OF THE 16TH INTERNATIONAL JOINT CONFERENCE ON COMPUTER VISION, IMAGING AND COMPUTER GRAPHICS THEORY AND APPLICATIONS - VOL. 4: VISAPP
Keywords
DocType
Citations 
Event-based Camera, Optical Flow Estimation, Ego-motion Data-sets, Frame Alignment
Conference
0
PageRank 
References 
Authors
0.34
0
4
Name
Order
Citations
PageRank
Mahmoud Khairallah100.34
Fabien Bonardi222.09
David Roussel301.01
Samia Bouchafa420.74