scholarly journals An intelligent video system for vehicle localization and tracking in police cars

Author(s):  
Amirali Jazayeri ◽  
Hongyuan Cai ◽  
Jiang Yu Zheng ◽  
Mihran Tuceryan ◽  
Herbert Blitzer
2021 ◽  
Vol 7 (12) ◽  
pp. 270
Author(s):  
Daniel Tøttrup ◽  
Stinus Lykke Skovgaard ◽  
Jonas le Fevre Sejersen ◽  
Rui Pimentel de Figueiredo

In this work we present a novel end-to-end solution for tracking objects (i.e., vessels), using video streams from aerial drones, in dynamic maritime environments. Our method relies on deep features, which are learned using realistic simulation data, for robust object detection, segmentation and tracking. Furthermore, we propose the use of rotated bounding-box representations, which are computed by taking advantage of pixel-level object segmentation, for improved tracking accuracy, by reducing erroneous data associations during tracking, when combined with the appearance-based features. A thorough set of experiments and results obtained in a realistic shipyard simulation environment, demonstrate that our method can accurately, and fast detect and track dynamic objects seen from a top-view.


Sensors ◽  
2021 ◽  
Vol 21 (9) ◽  
pp. 3286
Author(s):  
Yunlei Zhang ◽  
Xiaolin Gong ◽  
Kaihua Liu ◽  
Shuai Zhang

State-of-the-art radio frequency identification (RFID)-based indoor autonomous vehicles localization methods are mostly based on received signal strength indicator (RSSI) measurements. However, the accuracy of these methods is not high enough for real-world scenarios. To overcome this problem, a novel dual-frequency phase difference of arrival (PDOA) ranging-based indoor autonomous vehicle localization and tracking scheme was developed. Firstly, the method gets the distance between the RFID reader and the tag by dual-frequency PDOA ranging. Then, a maximum likelihood estimation and semi-definite programming (SDP)-based localization algorithm is utilized to calculate the position of the autonomous vehicles, which can mitigate the multipath ranging error and obtain a more accurate positioning result. Finally, vehicle traveling information and the position achieved by RFID localization are fused with a Kalman filter (KF). The proposed method can work in a low-density tag deployment environment. Simulation experiment results showed that the proposed vehicle localization and tracking method achieves centimeter-level mean tracking accuracy.


2012 ◽  
Vol 17 (4) ◽  
pp. 217-222
Author(s):  
Piotr Szymczyk ◽  
Magdalena Szymczyk

Abstract In this paper authors describe in details a system dedicated to scene configuration. The user can define different important 2D regions of the scene. There is a possibility to define the following kinds of regions: flour, total covering, down covering, up covering, middle covering, entrance/exit, protected area, prohibited area, allowed direction, prohibited direction, reflections, moving objects, light source, wall and sky. The definition of this regions is very important to further analysis of live stream camera data in the guardian video system.


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