Computer Science ›› 2021, Vol. 48 ›› Issue (3): 40-49.doi: 10.11896/jsjkx.201100186

Special Issue: Advances on Multimedia Technology

• Advances on Multimedia Technology • Previous Articles     Next Articles

Advances on Visual Object Tracking in Past Decade

ZHANG Kai-hua, FAN Jia-qing, LIU Qing-shan   

  1. Jiangsu Key Laboratory of Big Data Analysis Technology,Nanjing University of Information Science and Technology,Nanjing 210044,China
  • Received:2020-11-26 Revised:2021-01-02 Online:2021-03-15 Published:2021-03-05
  • About author:ZHANG Kai-hua,born in 1983,Ph.D,professor.His main research interests include image segmentation,level sets and visual tracking.
  • Supported by:
    National Major Project of China for New Generation of AI(2018AAA0100400),National Natural Science Foundation of China(61872189) and 333 High-level Talents Cultivation Project of Jiangsu Province(BRA2020291).

Abstract: Visual object tracking is a task in which the target region of the first frame in a video sequence is given,and then the target area is automatically matched in subsequent frames.Generally speaking,due to the complex factors such as scene occlusion,illumination change and object deformation,the appearance of the target and scene will change dramatically,which makes the tracking task itself is extremely challenging.In the past decade,with the extensive application of deep learning in the field of computer vision,the field of target tracking has also developed rapidly,resulting in a series of excellent algorithms.In view of this rapid development stage,this paper aims to provide a comprehensive review of visual object tracking research,mainly including the following aspects:the improvement of the basic framework of tracking,the improvement of target representation,the improvement of spatial context,the improvement of temporal context,the improvement of data sets and evaluation indicators.This paper also analyzes the advantages and disadvantages of these methods,and puts forward the possible future research trends.

Key words: Computer vision, Deep learning, Visual object tracking

CLC Number: 

  • TP391
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