A Novel Track Association Method Based on Overlapping Clustering and Evidence Combination

2021 ◽  
Author(s):  
Xinxin Shen ◽  
Xinyang Deng ◽  
Wen Jiang
Keyword(s):  
Overlapping Clustering ◽  
Evidence Combination ◽  
Track Association ◽  
Association Method

scholarly journals A track-to-track association method for automotive perception systems

2012 ◽  
Author(s):  
Adam Houenou ◽  
Philippe Bonnifait ◽  
Veronique Cherfaoui ◽  
Jean-Francois Boissou
Keyword(s):  
Track Association ◽  
Association Method

Multi-target Point-Track Association Method Based on Q-learning

2021 ◽  
Author(s):  
Gu Xiangqi ◽  
Xiong Wei ◽  
Cui Yaqi ◽  
Xiong Zhenyu ◽  
Kong Zhan ◽  
...  
Keyword(s):  
Target Point ◽  
Q Learning ◽  
Track Association ◽  
Association Method

Choosing a track association method

2002 ◽  
Vol 3 (2) ◽  
pp. 119-133 ◽  
Author(s):  
Barbara F. La Scala ◽  
Alfonso Farina
Keyword(s):  
Track Association ◽  
Association Method

Improved Estimate-to-Track Association Method for Track Continuity

2011 ◽  
Vol 467-469 ◽  
pp. 806-811
Author(s):  
Cheng Ouyang ◽  
Hong Bing Ji ◽  
Jun Gen Zhang
Keyword(s):  
Likelihood Ratios ◽  
Excellent Performance ◽  
Probability Hypothesis Density ◽  
Current State ◽  
Log Likelihood ◽  
Track Association ◽  
Finite Set ◽  
Simulation Results ◽  
Target States ◽  
Association Method

The probability hypothesis density (PHD) filter is a practical alternative to the optimal Bayesian multi-target filter based on finite set statistics. However, the PHD filter keeps no record of target identities and hence does not produce track-valued estimates of individual targets. To solve this problem, an improved estimate-to-track association method for track continuity is proposed in this paper. Firstly, a multi-step prediction of current target states is made, and then the weighted labels are assigned to them according to the inertia. Secondly, the fuzzy membership degrees of the current state estimates belonging to the tracks are obtained by utilizing the maximum entropy fuzzy clustering. Finally, the tracks are maintained by integrating all this information. Different from the traditional estimate-to-track association method, the proposed algorithm does not update the track information by simply summing the log likelihood ratios between adjacent scans, but take the entire multi-scan information into account by the operations such as weighting and clustering. The simulation results show that the proposed algorithm can maintain target tracks more accurately, even when the targets cross each other, implying strong robustness and excellent performance of track continuity.

Was Jung the first to diagnose "complexes" with the word-association method

1982 ◽  
Author(s):  
Michael Wertheimer
Keyword(s):  
Word Association ◽  
Association Method

Data association method of SLAM based on ant colony algorithm

2009 ◽  
Vol 29 (1) ◽  
pp. 136-138 ◽  
Author(s):  
Wen-jing ZENG ◽  
Tie-dong ZHANG ◽  
Yu-ru XU ◽  
Da-peng JIANG
Keyword(s):  
Ant Colony Algorithm ◽  
Data Association ◽  
Ant Colony ◽  
Association Method

An Overlapping Clustering Approach for Precision, Diversity and Novelty-Aware Recommendations

2021 ◽  
pp. 114917
Author(s):  
Chems Eddine Berbague ◽  
Nour El-islam Karabadji ◽  
Hassina Seridi ◽  
Panagiotis Symeonidis ◽  
Yannis Manolopoulos ◽  
...  
Keyword(s):  
Overlapping Clustering ◽  
Clustering Approach

Prediction of class and property assertions on OWL ontologies through evidence combination

2011 ◽  
Author(s):  
Giuseppe Rizzo ◽  
Nicola Fanizzi ◽  
Claudia d'Amato ◽  
Floriana Esposito
Keyword(s):  
Evidence Combination
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