Online Discrete Anchor Graph Hashing for Mobile Person Re-Identification

With the advance of mobile technologies, mobile devices such as unmanned aerial vehicle (UAV) become more important in video surveillance. By applying mobile person re-identification (re-id), mobile devices can monitor pedestrians in the transportation system from complex environments. Since the computing and storage resources of mobile devices are limited, traditional person re-id methods are not appropriate for mobile condition. Besides, mobile person re-id task also requires real-time processing. In this paper, we propose a novel hashing method: online discrete anchor graph hashing (ODAGH) for mobile person re-id. ODAGH integrates the advantages of online learning and hashing technology. In ODAGH, we propose an online discrete optimization algorithm to improve the efficiency of anchor graph learning in the online scenario. Experimental results demonstrate the superiority of ODAGH in terms of both effect and efficiency.

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Design of facial recognition system implemented in an unmanned aerial vehicle for citizen security in Latin America

ITM Web of Conferences ◽

10.1051/itmconf/20192704002 ◽

2019 ◽

Vol 27 ◽

pp. 04002

Author(s):

Diego Herrera ◽

Hiroki Imamura

Keyword(s):

Neural Network ◽

Latin America ◽

Deep Learning ◽

Mobile Devices ◽

Unmanned Aerial Vehicle ◽

Facial Recognition ◽

Recognition System ◽

Criminal Records ◽

Aerial Vehicle ◽

Facial Recognition System

In the new technological era, facial recognition has become a central issue for a great number of engineers. Currently, there are a great number of techniques for facial recognition, but in this research, we focus on the use of deep learning. The problems with current facial recognition convection systems are that they are developed in non-mobile devices. This research intends to develop a Facial Recognition System implemented in an unmanned aerial vehicle of the quadcopter type. While it is true, there are quadcopters capable of detecting faces and/or shapes and following them, but most are for fun and entertainment. This research focuses on the facial recognition of people with criminal records, for which a neural network is trained. The Caffe framework is used for the training of a convolutional neural network. The system is developed on the NVIDIA Jetson TX2 motherboard. The design and construction of the quadcopter are done from scratch because we need the UAV for adapt to our requirements. This research aims to reduce violence and crime in Latin America.

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A Cauchy mutant pigeon-inspired optimization–based multi-unmanned aerial vehicle path planning method

Measurement and Control ◽

10.1177/0020294019885155 ◽

2020 ◽

Vol 53 (1-2) ◽

pp. 83-92 ◽

Cited By ~ 3

Author(s):

Bo Hang Wang ◽

Dao Bo Wang ◽

Zain Anwar Ali

Keyword(s):

Path Planning ◽

Unmanned Aerial Vehicle ◽

Optimization Algorithm ◽

Vehicle Group ◽

Flight Duration ◽

Planning Strategy ◽

Optimum Position ◽

Cauchy Mutation ◽

Aerial Vehicle ◽

Vehicle Path

To improve the performance of multi-unmanned aerial vehicle path planning in plateau narrow area, a control strategy based on Cauchy mutant pigeon-inspired optimization algorithm is proposed in this article. The Cauchy mutation operator is chosen to improve the pigeon-inspired optimization algorithm by comparing and analyzing the changing trend of fitness function of the local optimum position and the global optimum position when dealing with unmanned aerial vehicle path planning problems. The plateau topography model and plateau wind field model are established. Furthermore, a variety of control constrains of unmanned aerial vehicles are summarized and modeled. By combining with relative positions and total flight duration, a cooperative path planning strategy for unmanned aerial vehicle group is put forward. Finally, the simulation results show that the proposed Cauchy mutant pigeon-inspired optimization method gives better robustness and cooperative path planning strategy which are effective and advanced as compared with traditional pigeon-inspired optimization algorithm.

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Cuttlefish Optimization Algorithm in Autotuning of Altitude Controller of Unmanned Aerial Vehicle (UAV)

ROBOT 2017: Third Iberian Robotics Conference - Advances in Intelligent Systems and Computing ◽

10.1007/978-3-319-70833-1_68 ◽

2017 ◽

pp. 841-852 ◽

Cited By ~ 2

Author(s):

Wojciech Giernacki ◽

Tadeo Espinoza Fraire ◽

Piotr Kozierski

Keyword(s):

Unmanned Aerial Vehicle ◽

Optimization Algorithm ◽

Aerial Vehicle

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Recommendations for UAV Pre-Flight Preparation

Elektrotekhnologii i elektrooborudovanie v APK ◽

10.22314/2658-4859-2020-67-1-93-98 ◽

2020 ◽

Vol 67 (1) ◽

pp. 93-98 ◽

Cited By ~ 1

Author(s):

Rashid K. Kurbanov ◽

Olga M. Zakharova

Keyword(s):

Unmanned Aerial Vehicles ◽

Unmanned Aerial Vehicle ◽

Visual Inspection ◽

Weather Conditions ◽

Aerial Vehicles ◽

Safety Research ◽

Aerial Vehicle ◽

Test Flight ◽

And Storage ◽

Measuring Unit

The current level of technical development and accessibility allows to consider unmanned aerial vehicles as a reliable tool for operational monitoring of agricultural territories. Drones are able to observe territories that are inaccessible to helicopters and small aircrafts. The use of drones is associated with certain risks that affect flight safety. (Research purpose) To make recommendations on the preflight preparation of unmanned aerial vehicles. (Materials and methods) The authors used scientific literature, survey materials of domestic and foreign authors, websites of UAV manufacturers. (Results and discussion) The authors examined the issues of a drone registration, key parameters that influence data collection and ensure safe monitoring: operation and storage of drone batteries, visual inspection of a drone, sensors calibration, setting the “return home” point and checking the signal GPS/GLONASS communication quality, test flight, restricted areas and weather conditions. (Conclusions) It was established that UAV pre-flight preparation was an important stage in monitoring agricultural fields, which included a number of operations that were carried out with the aim of ensuring the safety of the operator and the unmanned aerial vehicle, as well as to obtain high-quality aerial photography materials. The authors determined that an unmanned aerial vehicle weighing from 250 grams to 30 kilograms was a object to be registered. They identified the need for specialized software, compliance with the rules of operation and storage of batteries, a thorough visual inspection of the drone, calibration of the compass; checking the setting of the return point to the beginning of the route, the GPS/GLONASS signal level, conducting a test flight, monitoring the readings of the inertial measuring unit and weather conditions, checking the zone of prohibited flights.

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