Orthogonal Single-Target Tracking

In this study, we propose a novel Wasserstein distributional tracking method that can balance approximation with accuracy in terms of Monte Carlo estimation. To achieve this goal, we present three different systems: sliced Wasserstein-based (SWT), projected Wasserstein-based (PWT), and orthogonal co...

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Bibliographic Details
Main Authors: Kim, Y. (Author), Kwon, J. (Author)
Format: Article
Language:English
Published: Institute of Electrical and Electronics Engineers Inc. 2022
Subjects:
Online Access:View Fulltext in Publisher
LEADER 02339nam a2200373Ia 4500
001 10.1109-ACCESS.2022.3162200
008 220425s2022 CNT 000 0 und d
020 |a 21693536 (ISSN) 
245 1 0 |a Orthogonal Single-Target Tracking 
260 0 |b Institute of Electrical and Electronics Engineers Inc.  |c 2022 
856 |z View Fulltext in Publisher  |u https://doi.org/10.1109/ACCESS.2022.3162200 
520 3 |a In this study, we propose a novel Wasserstein distributional tracking method that can balance approximation with accuracy in terms of Monte Carlo estimation. To achieve this goal, we present three different systems: sliced Wasserstein-based (SWT), projected Wasserstein-based (PWT), and orthogonal coupled Wasserstein-based (OCWT) visual tracking systems. Sliced Wasserstein-based visual trackers can find accurate target configurations using the optimal transport plan, which minimizes the discrepancy between appearance distributions described by the estimated and ground truth configurations. Because this plan involves a finite number of probability distributions, the computation costs can be considerably reduced. Projected Wasserstein-based and orthogonal coupled Wasserstein-based visual trackers further enhance the accuracy of visual trackers using bijective mapping functions and orthogonal Monte Carlo, respectively. Experimental results demonstrate that our approach can balance computational efficiency with accuracy, and the proposed visual trackers outperform other state-of-the-art visual trackers on several benchmark visual tracking datasets. © 2013 IEEE. 
650 0 4 |a Computation costs 
650 0 4 |a Computational efficiency 
650 0 4 |a Computer vision 
650 0 4 |a Computer vision 
650 0 4 |a distance measurement 
650 0 4 |a Finite number 
650 0 4 |a Ground truth 
650 0 4 |a Monte Carlo methods 
650 0 4 |a Monte-Carlo estimation 
650 0 4 |a Optimal transport 
650 0 4 |a Orthogonal functions 
650 0 4 |a probability distribution 
650 0 4 |a Probability distributions 
650 0 4 |a Probability: distributions 
650 0 4 |a Single target tracking 
650 0 4 |a Target configurations 
650 0 4 |a Target tracking 
650 0 4 |a Tracking method 
650 0 4 |a Visual tracking systems 
700 1 |a Kim, Y.  |e author 
700 1 |a Kwon, J.  |e author 
773 |t IEEE Access