Object Tracking Method via Spatio-Temporal Context and Inverse Sparse Model
ZHAO Junqi
WU Hailong
LIU Jie
LIU Chaorong
Abstract：Aiming at the low accuracy problem in tracking methods based on the inverse sparse representation,an improved tracking method combining the spatio-temporal context with the inverse sparse representation is proposed. First of all,the partial fil?ter method is used to generate candidates with the object template. Then,spatio-temporal context confidence is adopted to optimize the candidates. Finally,tracking result is gotten by the inverse sparse representation with the candidates and target template. The ex?periment results validate the proposed method's performance.
Keywords：object trackinginverse sparse modelspatio-temporal contextparticle filter
Publication Date：2019-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：6( 3015-3019,3024 )