Open AccessResearch and Implementation of Object Tracking
Author(s) -
Jin Tian,
Guanglong Wang,
Weiwei Gao,
Dan Fang
Publication year - 2020
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.179
H-Index - 26
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/440/4/042098
Subject(s) - robustness (evolution) , computer science , artificial intelligence , video tracking , feature (linguistics) , matlab , computer vision , feature matching , similarity (geometry) , tracking (education) , pattern recognition (psychology) , object (grammar) , algorithm , feature extraction , image (mathematics) , psychology , pedagogy , biochemistry , chemistry , linguistics , philosophy , gene , operating system
Aiming at the problems that the traditional MeanShift has a singleness feature, this paper introduces depth feature based on binocular vision, thus proposes a depth feature based real-time MeanShift tracking algorithm. Firstly, a similarity measurement method based on advanced quadratic-form distance is put forward. Secondly, the self-adaptive adjustment mechanism of feature weight coefficient and updating strategy of object model are improved based on the color and depth features. Finally, the algorithm is simulated by Matlab. Results show that the proposed algorithm performs well in tracking accuracy, robustness.