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Multimedia Systems
Erschienen in: Multimedia Systems 3/2017

30.10.2015 | Regular Paper

Online visual tracking based on subspace representation with continuous occlusion modeling

verfasst von: Chunjuan Bo, Junxing Zhang, Changhong Liu, Qiang Yao

Erschienen in: Multimedia Systems | Ausgabe 3/2017

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Abstract

As an important issue in image processing and computer vision, online visual tracking acts a critical role in numerous lines of research and has many potential applications. This paper presents a novel tracking algorithm based on subspace representation with continuous occlusion handling, the contributions of which are threefolds. First, this paper develops an effective objective function to represent the tracked object, in which the object reconstruction, the sparsity of the error term and the spatial consistency of the error term are simultaneously considered. Then, we derive an iterative algorithm to solve the proposed objective function based on the accelerated proximal gradient framework, and therefore obtain the optimal representation coefficients and the possible occlusion conditions. Finally, based on the proposed representation model, we design an effective likelihood function and a simple model update scheme for building a robust tracker within the particle filter framework. We conduct many experiments to evaluate the proposed tracking algorithm in comparisons with other state-of-the-art trackers. Both qualitative and quantitative evaluations demonstrate the proposed tracker achieves good performance.
Vorheriger Artikel Self-representation graph feature selection method for classification
Nächster Artikel 3-D human pose recovery using nonrigid point set registration and body part tracking of depth data

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Fußnoten
2
The precision plot indicates the percentage of frames whose center location error (CLE) is within the given threshold, and the precision score is given by the score on a selected representative threshold (e.g., 20 pixels). In addition, the success plot demonstrates the ratio of successful frames whose overlap rate is larger than the given threshold, and the success score is evaluated by the area under curve (AUC).
 
3
We note that the APGL1, MTT, IVT and our methods are all belong to the “linear representation”-based tracking methods.
 
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Metadaten
Titel
Online visual tracking based on subspace representation with continuous occlusion modeling
verfasst von
Chunjuan Bo
Junxing Zhang
Changhong Liu
Qiang Yao
Publikationsdatum
30.10.2015
Verlag
Springer Berlin Heidelberg
Erschienen in
Multimedia Systems / Ausgabe 3/2017
Print ISSN: 0942-4962
Elektronische ISSN: 1432-1882
DOI
https://doi.org/10.1007/s00530-015-0496-z

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