scholarly journals Visual Tracking in Cluttered Environments Using the Visual Probabilistic Data Association Filter

2006 ◽  
Vol 22 (6) ◽  
pp. 1292-1297 ◽  
Author(s):  
Cheng-Ming Huang ◽  
David Liu ◽  
Li-Chen Fu
Keyword(s):  
Visual Tracking ◽  
Data Association ◽  
Probabilistic Data ◽  
Probabilistic Data Association ◽  
Cluttered Environments

scholarly journals Performance Study of Distance-Weighting Approach with Loopy Sum-Product Algorithm for Multi-Object Tracking in Clutter

Sensors ◽  
2021 ◽  
Vol 21 (7) ◽  
pp. 2544
Author(s):  
Pranav U. Damale ◽  
Edwin K. P. Chong ◽  
Tian J. Ma
Keyword(s):  
Performance Metrics ◽  
Data Association ◽  
Computation Time ◽  
False Alarms ◽  
Performance Study ◽  
Tracking Accuracy ◽  
Probabilistic Data ◽  
Probabilistic Data Association ◽  
Cluttered Environments ◽  
Distance Weighting

In this paper, we explore the performance of the distance-weighting probabilistic data association (DWPDA) approach in conjunction with the loopy sum-product algorithm (LSPA) for tracking multiple objects in clutter. First, we discuss the problem of data association (DA), which is to infer the correspondence between targets and measurements. DA plays an important role when tracking multiple targets using measurements of uncertain origin. Second, we describe three methods of data association: probabilistic data association (PDA), joint probabilistic data association (JPDA), and LSPA. We then apply these three DA methods for tracking multiple crossing targets in cluttered environments, e.g., radar detection with false alarms and missed detections. We are interested in two performance metrics: tracking accuracy and computation time. LSPA is known to be superior to PDA in terms of the former and to dominate JPDA in terms of the latter. Last, we consider an additional DA method that is a modification of PDA by incorporating a weighting scheme based on distances between position estimates and measurements. This distance-weighting approach, when combined with PDA, has been shown to enhance the tracking accuracy of PDA without significant change in the computation burden. Since PDA constitutes a crucial building block of LSPA, we hypothesize that DWPDA, when integrated with LSPA, would perform better under the two performance metrics above. Contrary to expectations, the distance-weighting approach does not enhance the performance of LSPA, whether in terms of tracking accuracy or computation time.

scholarly journals A Novel Probabilistic Data Association for Target Tracking in a Cluttered Environment

Sensors ◽  
2016 ◽  
Vol 16 (12) ◽  
pp. 2180 ◽  
Author(s):  
Xiao Chen ◽  
Yaan Li ◽  
Yuxing Li ◽  
Jing Yu ◽  
Xiaohua Li
Keyword(s):  
Target Tracking ◽  
Data Association ◽  
Probabilistic Data ◽  
Probabilistic Data Association ◽  
Cluttered Environment
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