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Special Issue "Multi-Sensor Systems for Object Tracking—2nd Edition"

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Remote Sensors".

Deadline for manuscript submissions: closed (10 September 2023) | Viewed by 3875

Special Issue Editor

Department of Applied Computer Science, AGH University of Science and Technology, 30-059 Kraków, Poland
Interests: pattern recognition; signal processing; computer vision
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Homogenous and heterogeneous multi-sensor systems are among the most popular and affordable solutions for object tracking. Sensor-based object tracking can be applied not only to individuals (motion capture, wearable sensors) and autonomous vehicles (self-driving cars and robots), but also to the monitoring of personnel and traffic flow in flats, buildings or even whole cities. Depending on the application, these sensors might be vision-based, inertial measurement units (IMUs), LIDARs, and many others.

This Special Issue aim to represent the latest advances in multi-sensor systems for object tracking. We welcome contributions in all fields of sensor-based object tracking, including new systems, signal processing algorithms, as well as new applications. These include but are not limited to:

  • Simultaneous localization and mapping (SLAM);
  • Motion capture;
  • Autonomous vehicles;
  • Ubiquitous sensors;
  • Wearable sensors;
  • Computer vision;
  • Inertial measurement units (IMUs);
  • High-energy particles detection with CCD cameras;

Dr. Tomasz Hachaj
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • object tracking
  • simultaneous localization and mapping (SLAM)
  • motion capture
  • autonomous vehicles
  • ubiquitous sensors
  • wearable sensors
  • computer vision
  • inertial measurement units (IMU)
  • high-energy particles
  • LIDAR

Published Papers (2 papers)

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Research

Article
Road Risk-Index Analysis Using Satellite Products
Sensors 2023, 23(5), 2751; https://doi.org/10.3390/s23052751 - 02 Mar 2023
Cited by 1 | Viewed by 1670
Abstract
This paper proposes a service called intelligent routing using satellite products (IRUS) that can be used in order to analyze risks to the road infrastructure during bad weather conditions, such as heavy rainfall, storms, or floods. By diminishing movement risk, rescuers can arrive [...] Read more.
This paper proposes a service called intelligent routing using satellite products (IRUS) that can be used in order to analyze risks to the road infrastructure during bad weather conditions, such as heavy rainfall, storms, or floods. By diminishing movement risk, rescuers can arrive safely at their destination. To analyze these routes, the application uses both data provided by Sentinel satellites from the Copernicus program and meteorological data from local weather stations. Moreover, the application uses algorithms to determine the night driving time. From this analysis we obtain a risk index for each road provided by Google Maps API and then we present the path alongside the risk index in a friendly graphic interface. In order to obtain an accurate risk index, the application analyzes both recent and past data (up to 12 months). Full article
(This article belongs to the Special Issue Multi-Sensor Systems for Object Tracking—2nd Edition)
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Article
Potential Obstacle Detection Using RGB to Depth Image Encoder–Decoder Network: Application to Unmanned Aerial Vehicles
Sensors 2022, 22(17), 6703; https://doi.org/10.3390/s22176703 - 05 Sep 2022
Cited by 2 | Viewed by 1650
Abstract
In this work, a new method is proposed that allows the use of a single RGB camera for the real-time detection of objects that could be potential collision sources for Unmanned Aerial Vehicles. For this purpose, a new network with an encoder–decoder architecture [...] Read more.
In this work, a new method is proposed that allows the use of a single RGB camera for the real-time detection of objects that could be potential collision sources for Unmanned Aerial Vehicles. For this purpose, a new network with an encoder–decoder architecture has been developed, which allows rapid distance estimation from a single image by performing RGB to depth mapping. Based on a comparison with other existing RGB to depth mapping methods, the proposed network achieved a satisfactory trade-off between complexity and accuracy. With only 6.3 million parameters, it achieved efficiency close to models with more than five times the number of parameters. This allows the proposed network to operate in real time. A special algorithm makes use of the distance predictions made by the network, compensating for measurement inaccuracies. The entire solution has been implemented and tested in practice in an indoor environment using a micro-drone equipped with a front-facing RGB camera. All data and source codes and pretrained network weights are available to download. Thus, one can easily reproduce the results, and the resulting solution can be tested and quickly deployed in practice. Full article
(This article belongs to the Special Issue Multi-Sensor Systems for Object Tracking—2nd Edition)
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