scholarly journals Detection Accuracy of Soccer Players in Aerial Images Captured from Several Viewpoints

2019 ◽  
Vol 4 (1) ◽  
pp. 9
Author(s):  
Takuro Oki ◽  
Ryusuke Miyamoto ◽  
Hiroyuki Yomo ◽  
Shinsuke Hara
Keyword(s):  
Global Positioning System ◽  
Sensor Nodes ◽  
Aerial Images ◽  
Aerial Image ◽  
Detection Accuracy ◽  
Received Signal Strength Indicator ◽  
Routing Schemes ◽  
High Speeds ◽  
Global Positioning ◽  
Player Detection

In the fields of professional and amateur sports, players’ health, physical and physiological conditions during exercise should be properly monitored and managed. The authors of this paper previously proposed a real-time vital-sign monitoring system for players using a wireless multi-hop sensor network that transmits their vital data. However, existing routing schemes based on the received signal strength indicator or global positioning system do not work well, because of the high speeds and the density of sensor nodes attached to players. To solve this problem, we proposed a novel scheme, image-assisted routing (IAR), which estimates the locations of sensor nodes using images captured from cameras mounted on unmanned aerial vehicles. However, it is not clear where the best viewpoints are for aerial player detection. In this study, the authors investigated detection accuracy from several viewpoints using an aerial-image dataset generated with computer graphics. Experimental results show that the detection accuracy was best when the viewpoints were slightly distant from just above the center of the field. In the best case, the detection accuracy was very good: 0.005524 miss rate at 0.01 false positive-per-image. These results are informative for player detection using aerial images and can facilitate to realize IAR.

Road Detection Based on Edge Feature with GAC Model in Aerial Image

2021 ◽  
Author(s):  
Linying Zhou ◽  
Zhou Zhou ◽  
Hang Ning
Keyword(s):  
Transformation Method ◽  
Aerial Images ◽  
Aerial Image ◽  
Initial Contour ◽  
Detection Accuracy ◽  
Road Detection ◽  
Canny Operator ◽  
The Road ◽  
Gradient Magnitude ◽  
Edge Feature

Road detection from aerial images still is a challenging task since it is heavily influenced by spectral reflectance, shadows and occlusions. In order to increase the road detection accuracy, a proposed method for road detection by GAC model with edge feature extraction and segmentation is studied in this paper. First, edge feature can be extracted using the proposed gradient magnitude with Canny operator. Then, a reconstructed gradient map is applied in watershed transformation method, which is segmented for the next initial contour. Last, with the combination of edge feature and initial contour, the boundary stopping function is applied in the GAC model. The road boundary result can be accomplished finally. Experimental results show, by comparing with other methods in [Formula: see text]-measure system, that the proposed method can achieve satisfying results.

Design of Urban Vehicle Dynamic and Real-Time Navigation System Based on WSNs, GPS, and GPRS Techniques

2013 ◽  
Vol 765-767 ◽  
pp. 3291-3294
Author(s):  
Cheng Lin Li ◽  
Zhi Yong Jiang
Keyword(s):  
Real Time ◽  
Global Positioning System ◽  
Navigation System ◽  
Traffic Congestion ◽  
Road Construction ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
General Packet Radio Service ◽  
Vehicle Navigation System ◽  
Global Positioning

Currently, the traffic congestion is a significant problem encountered in urban development, which should be resolved depending primarily on the management and deployment under the circumstance that road construction isn't able to keep the pace of automobile growth. WSNs (Wireless sensor networks), made up of numerous sensor nodes, form a multi-hop and self-organizing cellular system by wireless communication, which can realize real-time monitoring and collecting environmental information by cooperation. In this paper, a design of real-time and dynamic city vehicle navigation system is presented based on WSNs, GPS(Global Positioning System), and GPRS(General Packet Radio Service) techniques..

scholarly journals Multiple-Oriented and Small Object Detection with Convolutional Neural Networks for Aerial Image

2019 ◽  
Vol 11 (18) ◽  
pp. 2176 ◽  
Author(s):  
Chen ◽  
Zhong ◽  
Tan
Keyword(s):  
Neural Networks ◽  
Object Detection ◽  
Convolutional Neural Networks ◽  
Aerial Images ◽  
Superior Performance ◽  
Aerial Image ◽  
Detection Accuracy ◽  
Small Object ◽  
Data Set ◽  
Orientation Information

Detecting objects in aerial images is a challenging task due to multiple orientations and relatively small size of the objects. Although many traditional detection models have demonstrated an acceptable performance by using the imagery pyramid and multiple templates in a sliding-window manner, such techniques are inefficient and costly. Recently, convolutional neural networks (CNNs) have successfully been used for object detection, and they have demonstrated considerably superior performance than that of traditional detection methods; however, this success has not been expanded to aerial images. To overcome such problems, we propose a detection model based on two CNNs. One of the CNNs is designed to propose many object-like regions that are generated from the feature maps of multi scales and hierarchies with the orientation information. Based on such a design, the positioning of small size objects becomes more accurate, and the generated regions with orientation information are more suitable for the objects arranged with arbitrary orientations. Furthermore, another CNN is designed for object recognition; it first extracts the features of each generated region and subsequently makes the final decisions. The results of the extensive experiments performed on the vehicle detection in aerial imagery (VEDAI) and overhead imagery research data set (OIRDS) datasets indicate that the proposed model performs well in terms of not only the detection accuracy but also the detection speed.

A framework for indoor construction resources tracking by applying wireless sensor networks1This paper is one of a selection of papers in this Special Issue on Construction Engineering and Management.

2012 ◽  
Vol 39 (9) ◽  
pp. 1083-1088 ◽  
Author(s):  
Xuesong Shen ◽  
Ming Lu
Keyword(s):  
Radio Frequency Identification ◽  
Cost Effective ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Mobile Nodes ◽  
Received Signal Strength Indicator ◽  
Construction Engineering ◽  
Global Positioning ◽  
Frequency Identification ◽  
Selection Of

The state-of-the-art tracking technologies, such as the global positioning system (GPS) and the radio frequency identification (RFID), lend themselves well to applications in relatively open areas, while falling short of accuracy and reliability in indoor or partially covered application settings due to signal blockage, distortion or deterioration. This research aims to address this challenge in construction engineering by exploring a cost-effective positioning methodology to realize automated and continuous tracking of construction resources. The emerging ZigBee-based wireless sensor networks (WSN) technology is introduced. A framework of WSN application is proposed for indoor construction resources tracking, which consists of a group of stationary and mobile sensor nodes that can communicate with one another. Real-time locations of the mobile nodes can be determined by applying the localization method based on received signal strength indicator (RSSI) and geometric trilateration.

scholarly journals Match Demands of Women’s Collegiate Soccer

Sports ◽  
2020 ◽  
Vol 8 (6) ◽  
pp. 87
Author(s):  
Andrew R. Jagim ◽  
Jason Murphy ◽  
Alexis Q. Schaefer ◽  
Andrew T. Askow ◽  
Joel A. Luedke ◽  
...  
Keyword(s):  
Energy Expenditure ◽  
Global Positioning System ◽  
National Collegiate Athletic Association ◽  
Ncaa Division Iii ◽  
Fat Free Mass ◽  
Movement Kinematics ◽  
Division Iii ◽  
Match Play ◽  
High Speeds ◽  
Global Positioning

Research describing the match and specific positional demands during match play in women’s collegiate soccer is limited. The purpose of the study was to quantify the match demands of National Collegiate Athletic Association (NCAA) Division III soccer and assess position differences in movement kinematics, heart rate (HR), and energy expenditure. Twenty-five Division III women soccer players (height: 1.61 ± 0.3 m; body mass: 66.7 ± 7.5 kg; fat-free mass: 50.3 ± 6.5 kg; body fat%: 25.6 ± 5.1%) were equipped with a wearable global positioning system to assess the demands of 22 matches throughout a season. Players were categorized by position (goal keepers (GK), center defenders (CB), flank players (FP), forwards (F), and center midfielders (CM)). Players covered 9807 ± 2588 m and 1019 ± 552 m at high speeds (>249.6 m·m−1), with an overall average speed of 62.85 ± 14.7 m·m−1. This resulted in a mean HR of 74.2 ± 6% HR max and energy expenditure of 1259 ± 309 kcal. Significant and meaningful differences in movement kinematics were observed across position groups. CM covered the most distance resulting in the highest training load. FP covered the most distance at high speeds and mean HR values were highest in CM, CB, and FP positions.

scholarly journals TRANSLATING AERIAL IMAGES INTO STREET-MAP-LIKE REPRESENTATIONS FOR VISUAL SELF-LOCALIZATION OF UAVS

2019 ◽  
Vol XLII-2/W13 ◽  
pp. 575-580 ◽  
Author(s):  
M. Schleiss
Keyword(s):  
Global Positioning System ◽  
Global Navigation Satellite Systems ◽  
Aerial Imagery ◽  
Aerial Images ◽  
Visual Localization ◽  
Localization Accuracy ◽  
Satellite Systems ◽  
Global Positioning ◽  
Reference Map ◽  
Global Navigation Satellite

<p><strong>Abstract.</strong> Unmanned aerial vehicles (UAVs) rely on global navigation satellite systems (GNSS) like the Global Positioning System (GPS) for navigation but GNSS signals can be easily jammed. Therefore, we propose a visual localization method that uses a camera and data from Open Street Maps in order to replace GNSS. First, the aerial imagery from the onboard camera is translated into a map-like representation. Then we match it with a reference map to infer the vehicle’s position. An experiment over a typical sized mission area shows localization accuracy close to commercial GPS. Compared to previous methods ours is applicable to a broader range of scenarios. It can incorporate multiple types of landmarks like roads and buildings and it outputs absolute positions with higher frequency and confidence and can be used at altitudes typical for commercial UAVs. Our results show that the proposed method can serve as a backup to GNSS systems where suitable landmarks are available.</p>

scholarly journals Science and Technology in the Modern Agricultural Sector: An Overview

2021 ◽  
pp. 702-709
Author(s):  
Dr. S. Karthikeyan ◽  
Dr. M. Satheesh Pandian
Keyword(s):  
Global Positioning System ◽  
Agricultural Sector ◽  
Science And Technology ◽  
Aerial Images ◽  
Vertical Farming ◽  
Global Positioning ◽  
One Year ◽  
And Robotics ◽  
Livestock Rearing ◽  
Modern Technologies

Innovation is an important one in contemporary agricultural sector than ever before. Contemporary farming and agricultural activities work another way than those a few years ago, principally because of progressions in the science and technology, with sensors, devices, equipments, machines, and information technology. This sector, as a whole is facing huge confronts, from increasing costs of inputs, a scarcity of workers, and changing consumers’ preferences for lucidity and sustainability. There is mounting importance from agricultural corporations that solutions are desirable for these confronts. As a consequence recent agricultural sector habitually uses classy technologies like robotics, sensors for measuring temperature and moisture, aerial images, and global positioning system technology. In the last 10 years, application scientific technologies in the agricultural sector has witnessed a increment in the investment worth of 6.7 billion USD endowed in the last five years and attracted 1.9 billion USD in the last one year alone. These modern technologies and accurate modern agricultural and robotic systems permit businesses to be more gainful, competent, safer, and more eco friendly. Further these modern technologies have paying attention around different areas such as interior vertical farming, computerization and robotics, livestock rearing technology, up to date greenhouse farming practices, exactitude agricultural and artificial intelligence, and blockchain. With this backdrop the present paper made an attempt to explain applications of the science and technology in the modern agricultural sector.

scholarly journals Aerial Image Road Extraction Based on an Improved Generative Adversarial Network

2019 ◽  
Vol 11 (8) ◽  
pp. 930 ◽  
Author(s):  
Xiangrong Zhang ◽  
Xiao Han ◽  
Chen Li ◽  
Xu Tang ◽  
Huiyu Zhou ◽  
...  
Keyword(s):  
Law Enforcement ◽  
State Of The Art ◽  
Automated Detection ◽  
Aerial Images ◽  
Aerial Photographs ◽  
Aerial Image ◽  
Detection Accuracy ◽  
Road Extraction ◽  
Generative Adversarial Network ◽  
Adversarial Network

Aerial photographs and satellite images are one of the resources used for earth observation. In practice, automated detection of roads on aerial images is of significant values for the application such as car navigation, law enforcement, and fire services. In this paper, we present a novel road extraction method from aerial images based on an improved generative adversarial network, which is an end-to-end framework only requiring a few samples for training. Experimental results on the Massachusetts Roads Dataset show that the proposed method provides better performance than several state of the art techniques in terms of detection accuracy, recall, precision and F1-score.

A Research on Locating AGV via RSS Signals

2019 ◽  
Vol 889 ◽  
pp. 418-424 ◽  
Author(s):  
Duy Anh Nguyen ◽  
Minh Khoi Huynh
Keyword(s):  
Global Positioning System ◽  
Industrial Revolution ◽  
Automated Guided Vehicles ◽  
Advanced Technology ◽  
Received Signal Strength Indicator ◽  
Know How ◽  
Fourth Industrial Revolution ◽  
Global Positioning ◽  
Production Manager ◽  
And Performance

We are now living in an era of advanced technology, where every part of daily life is related to each other via many kinds of wireless connection. The fourth industrial revolution is now heading toward many kinds of network connecting in real-time which can boost productivity and performance among many manufacturers. In particular, a production manager wanted to know how many automated guided vehicles (AGV) were deployed in a warehouse at that moment; modern farmers wanted to know how many harvesting robots were operating, etc. Therefore, navigating is one of the main elements to handle these tasks. Although we have already applied Global Positioning System (GPS) to the outdoors so far, they still had some limitations, especially on deploying between indoor like houses, buildings which GPS signals are unable to reach. In this paper, we proposed a technique in order to recognize AGV and the distance between them via Received Signal Strength Indicator (RSSI) technique. In addition, we developed a way to store these data on a server for last long usage.

Localization Schemes and Its Challenges in Underwater Wireless Sensor Networks

2020 ◽  
Vol 17 (6) ◽  
pp. 2750-2754
Author(s):  
Osho Gupta ◽  
Manni Kumar ◽  
Aadil Mushtaq ◽  
Nitin Goyal
Keyword(s):  
Global Positioning System ◽  
Environmental Changes ◽  
Sea Water ◽  
Vital Role ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Dense Medium ◽  
Stable Configuration ◽  
Network Simulator ◽  
Global Positioning

An underwater wireless sensor network (UWSN) consists of numerous sensor nodes deployed below the water to monitor physical and environmental changes. But to locate the deployed sensor nodes is an issue. Global positioning system (GPS) doesn’t work below the water because of water depth and dense medium. Also manual and stable configuration of sensor nodes is not possible in case of UWSN due to water drift of 3 m/s. This gives the challenge of locating the sensor node to fetch data from that node. So, localization plays a vital role in many applications wherein the absence of GPS and manual configuration. Various localization schemes widespread motivation for the purpose of data tagging, node tracking and target detection. Here we are classifying various localization methods by which we can deploy various sensors under the deep sea water. Here, the authors have also compared some existing UWSN techniques with the help of network simulator to guide the research fraternity.

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