Login (DCU Staff Only)
Login (DCU Staff Only)

DORAS | DCU Research Repository

Explore open access research and scholarly works from DCU

Advanced Search

Utilising visual attention cues for vehicle detection and tracking

Hu, Feiyan orcid logoORCID: 0000-0001-7451-6438, Gurram Munirathnam, Venkatesh orcid logoORCID: 0000-0002-4393-9267, O'Connor, Noel E. orcid logoORCID: 0000-0002-4033-9135, Smeaton, Alan F. orcid logoORCID: 0000-0003-1028-8389 and Little, Suzanne orcid logoORCID: 0000-0003-3281-3471 (2021) Utilising visual attention cues for vehicle detection and tracking. In: 25th International Conference on Pattern Recognition (ICPR2020), 10-15 Jan 2021, Milan, Italy (Online).

Abstract
Advanced Driver-Assistance Systems (ADAS) have been attracting attention from many researchers. Vision-based sensors are the closest way to emulate human driver visual behaviour while driving. In this paper, we explore possible ways to use visual attention (saliency) for object detection and tracking. We investigate: 1) How a visual attention map such as a subjectness attention or saliency map and an objectness attention map can facilitate region proposal generation in a 2- stage object detector; 2) How a visual attention map can be used for tracking multiple objects. We propose a neural network that can simultaneously detect objects as and generate objectness and subjectness maps to save computational power. We further exploit the visual attention map during tracking using a sequential Monte Carlo probability hypothesis density (PHD) filter. The experiments are conducted on KITTI and DETRAC datasets. The use of visual attention and hierarchical features has shown a considerable improvement of ≈8% in object detection which effectively increased tracking performance by ≈4% on KITTI dataset.
Metadata
Item Type:Conference or Workshop Item (Paper)
Event Type:Conference
Refereed:Yes
Subjects:Computer Science > Artificial intelligence
Computer Science > Image processing
Computer Science > Information technology
Computer Science > Machine learning
Computer Science > Multimedia systems
DCU Faculties and Centres:DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing
DCU Faculties and Schools > Faculty of Engineering and Computing > School of Electronic Engineering
Research Initiatives and Centres > INSIGHT Centre for Data Analytics
Published in: 25th International Conference on Pattern Recognition, Proceedings. . Institute of Electrical and Electronics Engineers (IEEE).
Publisher:Institute of Electrical and Electronics Engineers (IEEE)
Official URL:https://www.micc.unifi.it/icpr2020/index.php/confe...
Copyright Information:© 2020 The Authors
Funders:Science Foundation Ireland grant numbers SFI/12/RC/2289 P2 and SFI/16/SP/3804.
ID Code:25181
Deposited On:11 Jan 2021 11:57 by Feiyan Hu . Last Modified 05 Aug 2021 10:27
Documents

Full text available as:

[thumbnail of ICPR2020_saliency_det_tracking.pdf]
Preview
PDF - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
4MB
Downloads

Downloads

Downloads per month over past year

Archive Staff Only: edit this record