Open AccessStable and salient patch‐based appearance model for robust object tracking
Author(s) -
Luo Bo,
Liang Chao,
Ruan Weijian,
Hu Ruimin
Publication year - 2016
Publication title -
electronics letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.375
H-Index - 146
eISSN - 1350-911X
pISSN - 0013-5194
DOI - 10.1049/el.2016.0122
Subject(s) - video tracking , salience (neuroscience) , artificial intelligence , computer science , computer vision , salient , tracking (education) , matching (statistics) , stability (learning theory) , object (grammar) , pattern recognition (psychology) , machine learning , mathematics , psychology , pedagogy , statistics
As a classic appearance modelling method in object tracking, patch‐based approach is believed to own natural superiority in handling local occlusion to its divide‐and‐conquer philosophy. However, in facing of more severe application conditions, such as heavy occlusion, part deformation and illumination change, traditional patch‐based method may also fail due to the lack of sufficient matching patches. To address this problem, temporal stability as well as spatial salience to collaboratively improve patch selection and update schemes, resulting in a robust tracking algorithm for more challenging scenarios are proposed. Both quantitative and qualitative experiments conducted on practical video sequences demonstrate the effectiveness of the proposed method.