Robust long-term object tracking with adaptive scale and rotation estimation
Open Access
- 1 March 2020
- journal article
- research article
- Published by SAGE Publications in International Journal of Advanced Robotic Systems
- Vol. 17 (2)
- https://doi.org/10.1177/1729881420909736
Abstract
In this article, a robust long-term object tracking algorithm is proposed. It can tackle the challenges of scale and rotation changes during the long-term object tracking for security robots. Firstly, a robust scale and rotation estimation method is proposed to deal with scale changes and rotation motion of the object. It is based on the Fourier–Mellin transform and the kernelized correlation filter. The object’s scale and rotation can be estimated in the continuous space, and the kernelized correlation filter is used to improve the estimation accuracy and robustness. Then a weighted object searching method based on the histogram and the variance is introduced to handle the problem that trackers may fail in the long-term object tracking (due to semi-occlusion or full occlusion). When the tracked object is lost, the object can be relocated in the whole image using the searching method, so the tracker can be recovered from failures. Moreover, two other kernelized correlation filters are learned to estimate the object’s translation and the confidence of tracking results, respectively. The estimated confidence is more accurate and robust using the dedicatedly designed kernelized correlation filter, which is employed to activate the weighted object searching module, and helps to determine whether the searching windows contain objects. We compare the proposed algorithm with state-of-the-art tracking algorithms on the online object tracking benchmark. The experimental results validate the effectiveness and superiority of our tracking algorithm.Keywords
Funding Information
- National Natural Science Foundation of China (No. 61503401)
This publication has 23 references indexed in Scilit:
- Visual Tracking via Sparse and Local Linear CodingIEEE Transactions on Image Processing, 2015
- Object Tracking BenchmarkIEEE Transactions on Pattern Analysis and Machine Intelligence, 2015
- High-Speed Tracking with Kernelized Correlation FiltersIEEE Transactions on Pattern Analysis and Machine Intelligence, 2014
- Fast Compressive TrackingIEEE Transactions on Pattern Analysis and Machine Intelligence, 2014
- A survey of appearance models in visual object trackingACM Transactions on Intelligent Systems and Technology, 2013
- Image Registration Using Log Polar Transform and Phase Correlation to Recover Higher ScaleJournal of Pattern Recognition Research, 2012
- Object trackingACM Computing Surveys, 2006
- A Survey on Visual Surveillance of Object Motion and BehaviorsIEEE Transactions on Systems, Man and Cybernetics, Part C (Applications and Reviews), 2004
- An FFT-based technique for translation, rotation, and scale-invariant image registrationIEEE Transactions on Image Processing, 1996
- Indexing via Color HistogramsPublished by Springer Science and Business Media LLC ,1992