.png){kind=icon}
Return
Multi-view region proposal network predictive learning for tracking
.png){kind=icon}
PRE
AI
DOI：10.1007/s00530-022-01001-w.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Visual tracking is one of the most challenging problems in computer vision. Most state-of-the-art visual trackers suffer from three challenging problems: nondiverse discriminate feature representation, coarse object locator, and limited quantities of positive samples. In this paper, a multi-view multi-expert region proposal prediction algorithm for tracking is proposed to solve the above problems concurrently in one framework. The proposed algorithm integrates multiple views and exploits powerful multiple sources of information, which can solve nondiverse discriminate feature representation problem effectively. It builds multiple SVM classifier models on the expanded bounding boxes and adds the regional suggestion network module to accurately optimize it to predict optimal object location, which naturally alleviates the coarse object locator and limited quantities of positive samples problems at the same time. A comprehensive evaluation of the proposed approach on various benchmark sequences has been performed. The evaluation results demonstrate our method can significantly improve the tracking performance by combining the advantages of lightweight region proposal network predictive learning model and multi-view expert groups. The experimental results demonstrate the proposed approach outperforms other state-of-the-art visual trackers.
Keywords:
Region proposal prediction
Multi-view multi-expert learning
Visual tracking
Prediction learning
Journal
IF:
3.1
Papers:
2.8K
Citations:
2.7K
Organization
No organization information available
Cited Papers
ShareSaveStudy of structural, dielectric, and impedance properties of lead-free Zr and Y Co-doped BaTiO3
PREAI
ShareSaveShareSavePTX encapsulated by an XG–DOX conjugate for combination therapy against multi-drug resistance.png)
RSC Advances
RSC AdvancesIF0
PREAI
ShareSaveShareSave
View more