Modeling the information completeness of object tracking systems

2011 ◽  
Vol 20 (3) ◽  
pp. 268-282 ◽  
Author(s):  
Cleopatra Bardaki ◽  
Panos Kourouthanassis ◽  
Katerina Pramatari
Keyword(s):  
Object Tracking ◽  
Tracking Systems

scholarly journals Quality of Radar Direction-Finding via Conical Scanning

2021 ◽  
Vol 24 (5) ◽  
pp. 50-65
Author(s):  
A. D. Pluzhnikov ◽  
L. V. Kogteva ◽  
E. N. Pribludova ◽  
S. B. Sidorov ◽  
E. G. Chuzhaykin
Keyword(s):  
Mathematical Modeling ◽  
Object Tracking ◽  
Statistical Processing ◽  
Direction Finding ◽  
Tracking Systems ◽  
Tracking Errors ◽  
Dynamic Tracking ◽  
Quantitative Results ◽  
Variance Estimate ◽  
Angular Coordinates

Introduction. Conical scanning is applied for optimizing hardware resources in new devices, as well as when upgrading existing systems. All this explains the relevance of studying this type of direction finding systems.Aim. To adjust and complement the known calculation relations for the variance of direction finding results – an indicator of the quality (accuracy) of direction finding, as well as to determine the possibilities of optimizing direction finding and automatic object tracking processes.Materials and methods. Factors limiting the accuracy of direction finding via conical scanning were analyzed using spectral analysis. Mathematical modeling followed by statistical processing of quantitative results makes it possible to determine the conditions under which the influence of certain factors is predominant, as well as the conditions under which adjustment (completion) of the known calculation relations is required. The specified conditions are the errors at which the objects of direction finding are tracked. New calculation relations for the mentioned adjustment were determined by the methods of statistical radio engineering.Results. The validity of the calculation relations found is confirmed by mathematical modeling. Calculations and modeling lead to the need to optimize parameters for automatic object tracking systems.Conclusion. The study shows that, when choosing parameters for auto-tracking systems with conical scanning, it is important to implement object tracking not with minimal, but rather with optimized tracking errors in angular coordinates, which are to be estimated during direction finding. Moreover, the optimized errors (the values of static errors and the most probable values of the dynamic tracking errors) will require adjustment of the known analytical estimates for the variance of the direction finding results – the qualitative indicator of the direction finder (accuracy indicator). The determined analytical relationships allow such an adjustment to be performed, leading to an increased variance estimate by 10 dB.

Experimenting WNN support in object tracking systems

2016 ◽  
Vol 183 ◽  
pp. 79-89 ◽  
Author(s):  
Massimo De Gregorio ◽  
Maurizio Giordano ◽  
Silvia Rossi ◽  
Mariacarla Staffa
Keyword(s):  
Object Tracking ◽  
Tracking Systems

Adaboost-Gaze Based Multi-Stage Object Tracking

2012 ◽  
Vol 246-247 ◽  
pp. 179-183
Author(s):  
Yu Bin Yang ◽  
Jiao Jiao Gu ◽  
Xiao Yu Zhang ◽  
Zhi Liu
Keyword(s):  
Computer Vision ◽  
Object Tracking ◽  
Important Application ◽  
Tracking Systems ◽  
Object Position ◽  
Automated Tracking ◽  
Multi Stage ◽  
Initial Object

Object tracking is a very important application in the fields of computer vision. In practice, automated tracking systems can rarely meet the required performance. This paper improves the attentional based tracking framework with Adaboost and gaze selection. The object classifier is implemented using the ADA Boosting to recognize digits from the MNIST dataset. At the initial object position Gaze selection is performed. The performance of the framework is evaluated using digit videos generated from the MNIST dataset with clutters. In general, the performance of the framework is robust to changes in motion routes and degree of clutter.

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