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Sensors 2018, 18(2), 653; https://doi.org/10.3390/s18020653

Adaptive Correlation Model for Visual Tracking Using Keypoints Matching and Deep Convolutional Feature

1
School of Optics and Photonics, Image Engineering & Video Technology Lab, Beijing Institute of Technology, Beijing 100081, China
2
Key Laboratory of Photoelectronic Imaging Technology and System, Ministry of Education of China, Beijing 100081, China
3
School of Information and Communication, Guangxi Key Laboratory of Wireless Wideband Communication and Signal Processing, Guilin University of Electronic Technology, Guilin 541004, China
*
Author to whom correspondence should be addressed.
Received: 7 November 2017 / Revised: 5 February 2018 / Accepted: 7 February 2018 / Published: 23 February 2018
(This article belongs to the Section Physical Sensors)
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Abstract

Although correlation filter (CF)-based visual tracking algorithms have achieved appealing results, there are still some problems to be solved. When the target object goes through long-term occlusions or scale variation, the correlation model used in existing CF-based algorithms will inevitably learn some non-target information or partial-target information. In order to avoid model contamination and enhance the adaptability of model updating, we introduce the keypoints matching strategy and adjust the model learning rate dynamically according to the matching score. Moreover, the proposed approach extracts convolutional features from a deep convolutional neural network (DCNN) to accurately estimate the position and scale of the target. Experimental results demonstrate that the proposed tracker has achieved satisfactory performance in a wide range of challenging tracking scenarios. View Full-Text
Keywords: correlation filter-based visual tracking; deep convolutional neural network; deep convolutional feature; keypoints matching; adaptive model updating correlation filter-based visual tracking; deep convolutional neural network; deep convolutional feature; keypoints matching; adaptive model updating
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Li, Y.; Xu, T.; Deng, H.; Shi, G.; Guo, J. Adaptive Correlation Model for Visual Tracking Using Keypoints Matching and Deep Convolutional Feature. Sensors 2018, 18, 653.

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