NDLI: Visual odometry particle filter for improving accuracy of visual object trackers

Content Provider	IET Digital Library
Author	Pak, J. M.
Abstract	This Letter proposes a novel state estimator called the visual odometry particle filter (VOPF) for improving accuracy of visual object trackers. For the VOPF, a novel visual odometry motion model that is better than the conventional constant velocity motion model is proposed. In addition, a new particle injection method to prevent sample impoverishment and the incorrect measurement detection method are proposed. Visual object tracking experiments using 30 visual object trackers demonstrate that the VOPF improves accuracy of the trackers and outperforms the conventional particle and Kalman filters using the CV motion model.
Starting Page	884
Ending Page	887
Page Count	4
ISSN	00135194
Volume Number	56
e-ISSN	1350911X
Issue Number	Issue 17, Aug (2020)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/el/56/17
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/el.2020.0374
Journal	Electronics Letters
Publisher Date	2020-06-30
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	30 Visual Object Trackers Computer Vision And Image Processing Technique Conventional Constant Velocity Motion Model Conventional Particle Distance Measurement Filtering Method in Signal Processing Image Recognition Kalman Filter Mobile Robots Object Detection Object Tracking Optical, Image And Video Signal Processing Particle Filter Particle Injection Method Robot And Manipulator Mechanics Robot Kinematics Spatial Variables Measurement State Estimation Statistics Target Tracking Visual Object Tracking Experiments Visual Odometry Particle Filter VOPF
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering

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