Vehicle Tracking Algorithm Based on Observation Feedback and Block Symmetry Particle Filter. (13th February 2014)
- Record Type:
- Journal Article
- Title:
- Vehicle Tracking Algorithm Based on Observation Feedback and Block Symmetry Particle Filter. (13th February 2014)
- Main Title:
- Vehicle Tracking Algorithm Based on Observation Feedback and Block Symmetry Particle Filter
- Authors:
- Hao, Yanshuang
Yin, Yixin
Lan, Jinhui - Other Names:
- Valimaki Vesa Academic Editor.
- Abstract:
- Abstract : This paper proposes a novel particle filter algorithm for vehicle tracking, which feeds observation information back to state model and integrates block symmetry into observation model. In view of the proposal distribution in traditional particle filter without considering the observation data, a new state transition model which takes the observation into account is presented, so that the allocation of particles is more familiar with the posterior distribution. To track the vehicles in background with similar colors or under partial occlusion, block symmetry is proposed and introduced into the observation model. Experimental results show that the proposed algorithm can improve the accuracy and robustness of vehicle tracking compared with traditional particle filter and Kernel Particle Filter.
- Is Part Of:
- Journal of electrical and computer engineering. Volume 2014(2014)
- Journal:
- Journal of electrical and computer engineering
- Issue:
- Volume 2014(2014)
- Issue Display:
- Volume 2014, Issue 2014 (2014)
- Year:
- 2014
- Volume:
- 2014
- Issue:
- 2014
- Issue Sort Value:
- 2014-2014-2014-0000
- Page Start:
- Page End:
- Publication Date:
- 2014-02-13
- Subjects:
- Computer engineering -- Periodicals
Electrical engineering -- Periodicals
621.3905 - Journal URLs:
- https://www.hindawi.com/journals/jece/ ↗
- DOI:
- 10.1155/2014/520342 ↗
- Languages:
- English
- ISSNs:
- 2090-0147
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD Digital store
- Ingest File:
- 10768.xml