Computer Science

Computer Science ›› 2023, Vol. 50 ›› Issue (11A): 221000172-6.doi: 10.11896/jsjkx.221000172

• Image Processing & Multimedia Technology • Previous Articles     Next Articles

Visual Object Tracking Based on Adaptive Search Range Adjustment

WANG Chao1,2, WANG Kai1   

  1. 1 School of Information and Electrical Engineering,Hebei University of Engineering,HeBei,Handan 056000,China
    2 Hebei Key Laboratory of Security & Protection Information Sensing and Processing,HeBei,Handan 056000,China
  • Published:2023-11-09
  • About author:WANG Chao,born in 1983,Ph.D,lecturer,master supervisor,is a member of China Computer Federation.His main research interests include video/image processing and computer vision.
  • Supported by:
    National Natural Science Foundation of China(62071071)and Science and Technology Plan Project of Handan(21422031251).

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Abstract: The mainstream visual object tracking algorithms generally set the position of object that tracked in the last frame as the center of a search range,which is used to detect the object in current frame.However,the tracking object may deviate from the center of search range due to its motion,thus its detection response in current frame can be easily inhibited by the cosine window penalty mechanism,which leads to tracking failure.To solve this problem,an adaptive search range adjustment(ASRA) method is proposed.In this method,a motion prediction model based on recurrent neural network(RNN) is used to predict the object position in current frame,and it is combined with the correlation filtering response to adjust the center of search range.The size of search range is further adjusted according to the motion vector of the tracking object.The proposed ASRA method is applied to current state-of-the-art object tracking algorithms based on Siamese networks.Experiments on OTB2015 and VOT2018 datasets show that ASRA can improve the accuracy and robustness of these algorithms.

Key words: Visual object tracking, Search range, Motion prediction, Correlation filtering, Siamese networks

CLC Number: 

  • TP391
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