drone detection kaggle

Proceedings of the International Conference on Computer Vision Systems. The Fcam is used to feed a foreground/background detector based on Gaussian Mixture Models (GMM), which produces binary masks of moving objects. This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository. F. Svanstrm, C. Englund, F. Alonso-Fernandez, Real-Time Drone Detection and Tracking with Visible, Thermal and Acoustic Sensors. If the dataset is to be used in another development environment, the label files can be opened in Matlab, and the content is saved in the desired format, such as .csv. Shi X., Yang C., Xie W., Liang C., Shi Z., Chen J. Anti-drone system with multiple surveillance technologies. The filenames start with the sensor type, followed by the target type and a number, e.g. The benchmarks section lists all benchmarks using a given dataset or any of Most of the existing studies on drone detection fail to specify the type of acquisition device, the drone type, the detection range, or the employed dataset. Fig. Three different drones are used to collect and compose the dataset: Hubsan H107D+, a small-sized first-person-view (FPV) drone, the high-performance DJI Phantom 4 Pro, and finally, the medium-sized kit drone DJI Flame Wheel in quadcopter (F450) configuration. The classes available with each type of sensor are indicated in Table1. The acquisition sensors are mounted on a pan-tilt platform that steers the cameras to the objects of interest. Based on this, the pan/tilt platform servos are then steered via the servo controller so that the moving object can be captured by the infrared and visible cameras. The clips are annotated with the filenames themselves, e.g. Given the resolution and field of view of the IRcam and the object class sizes: Drone 0.4m, bird 0.8m, helicopter110m and airplane220m, we get a distance division for the different object types summarized in Table4. Chevalier P. ResearchGate publication; 2016. These are of the following types: Hubsan H107D+, a small first-person-view (FPV) drone; the high-performance DJI Phantom 4 Pro; and the medium-sized DJI Flame Wheel. Papers With Code is a free resource with all data licensed under, UAV-Human: A Large Benchmark for Human Behavior Understanding with Unmanned Aerial Vehicles. of Mathematics, Computer Science and Physics, International Conference on Military Communications and Information Systems, A Comprehensive Approach to Countering Unmanned Aircraft Systems, Camera ready paper upload deadline: 10.06.2022. This is the Servocity DDT-560H direct drive tilt platform together with the DDP-125 Pan assembly, also from Servocity. Andrasi P. Night-time detection of UAVs using thermal infrared camera. IR_DRONE_001.mp4. The dataset was collected by a flying UAV in multiple urban and rural districts in both daytime and nighttime over three months, hence covering extensive diversities w.r.t subjects, backgrounds, illuminations, weathers, occlusions, camera motions, and UAV flying attitudes. about navigating our updated article layout. Dept. You signed in with another tab or window. To illustrate the detect, recognize, and identify concept, objects from all the target classes being 15 pixels in width are shown in Fig. explicitly telling what kind of helicopter it is and so on. There are 30 files of each of the three output audio classes indicated in Table1. Fig. aAir Defence Regiment, Swedish Armed Forces, Sweden, bCenter for Applied Intelligent Systems Research (CAISR), Halmstad University, Halmstad SE 301 18, Sweden, cRISE, Lindholmspiren 3A, Gothenburg SE 417 56, Sweden.

Whitepaper on thermal DRI. The raw format is used in the database to avoid the extra overlaid text information of the interpolated image. ICMCIS is again running a data challenge, releasing a dataset for interested participants to develop machine learning based solutions. The color palette can be changed for the interpolated image format, and several other image processing features are also available. The laptop is connected to all the sensors mentioned above and the servo controller using the built-in ports and an additional USB hub. The lack of proper UAV detection studies employing thermal infrared cameras is also acknowledged as an issue, despite its success in detecting other types of targets [2]. In that paper, the authors were able to detect three different drone types up to 100m. Gian Luca FORESTI, University of Udine, Dept. Link to thesis All computations are made on a standard laptop. This is because it has not been possible to film all types of suitable targets, given that this work has been carried out during the drastic reduction of flight operations due to the COVID19 pandemic. The site is secure. The .gov means its official. The data contained in the database can be used as-is without filtering or enhancement. When flying within airports' control zones or traffic information zones and if you do not fly closer than 5km from any section of the airport's runway(s), you may fly without clearance if you stay below 50m from the ground. YouTube channel VIRTUAL AIRFIELD operated by SK678387. All participants in this data challenge are invited to take part in the special session. The database is complemented with 90 audio files of the classes drones, helicopters and background noise. The dataset can be used to develop new algorithms for drone detection using multi-sensor fusion from infrared and visible videos and audio files. A Dataset for Multi-Sensor Drone Detection". The annotation of the video dataset is done using the Matlab video labeller app. Since the drones must be flown within visual range, the largest sensor-to-target distance for a drone is 200m. There are also eight clips (five IR and three visible videos) within the dataset with two drones flying simultaneously, as shown, for example, in Fig. Since one of the objectives of this work is to explore performance as a function of the sensor-to-target distance, the video dataset has been divided into three distance category bins: Close, Medium and Distant. The dataset can be used for multi-sensor drone detection and tracking. The data does not include human subjects or animals. Typical sensors are radar or radio direction finding, data from both types of sensor are included in the dataset. To address this issue, we develop a model-based drone augmentation technique that automatically generates drone images with a bounding box label on drones location. If nothing is detected by the Fcam, the platform can be set to move in two different search patterns to scan the sky around the system. The database includes three different drones, a small-sized model (Hubsan H107D+), a medium-sized drone (DJI Flame Wheel in quadcopter configuration), and a performance-grade model (DJI Phantom 4 Pro). Finally, we present an integrated detection and tracking system that outperforms the performance of each individual module containing detection or tracking only. 7 shows the main parts of the system. Both the videos and the audio files are cut into ten-second clips to be easier to annotate. Fernando Alonso-Fernandez: Conceptualization, Supervision, Funding acquisition, Writing original draft. We use variants to distinguish between results evaluated on The sensors employed are specified in the next section. It contains infrared and visible videos and audio files of drones, birds, airplanes, helicopters, and background sounds. Link to Data in Brief. A multi-object Kalman filter tracker then steers the infrared and visible cameras via a servo controller mounted on a pan/tilt platform. The sound of the distinct classes of the database is captured with a Boya BY-MM1 mini cardioid directional microphone, which is also connected to the laptop. Setup of the acquisition system. Stay informed on the latest trending ML papers with code, research developments, libraries, methods, and datasets. will also be available for a limited time. Therefore, the computational cost is relatively high, and hence a laptop with a separate GPU was used. The videos are recorded at locations in and around Halmstad and Falkenberg (Sweden), at Halmstad Airport (IATA code: HAD/ICAO code: ESMT), Gothenburg City Airport (GSE/ESGP) and Malm Airport (MMX/ESMS). For example, ImageNet 3232 The video part contains 650 infrared and visible videos (365 IR and 285 visible) of drones, birds, airplanes and helicopters. 2. "Svanstrm F. (2020). It might be possible to use a simple microcontroller if the drone detection system trained and evaluated with the dataset uses only one sensor or a small number of them. The distribution of the 285 visible videos. At this level, we can not only detect but also recognize the different objects, albeit without necessarily identifying them, i.e. Fredrik Svanstrm: Conceptualization, Methodology, Investigation, Data curation, Writing review & editing. TSFS 2017:110 Transportstyrelsens freskrifter om obemannade luftfartyg. Common birds appearing in the dataset are the rook (Corvus frugilegus) and the western jackdaw (Coloeus monedula) of the crow family (Corvidae), the European herring gull (Larus argentatus), the common gull (Larus canus) and the black-headed gull (Chroicocephalus ridibundus) of the Laridae family of seabirds. Pan/tilt motion is achieved with two Hitec HS-7955TG servos. The drone flights are all done in compliance with the Swedish national rules for unmanned aircraft found in [10]. The largest distance between the sensors and a drone in the database is 200m. All videos are in mp4 format. To record data in the visible range of the spectrum, a Sony HDR-CX405 video camera (Vcam) is used, which provides data through an HDMI port. "Svanstrm F, Englund C and Alonso-Fernandez F. (2020). All sensors and the platform are controlled with a standard laptop vis a USB hub. 6. Infiniteoptics. (a) An airplane at a distance of 1000m. (b) A bird at a distance of 40m. (c) A drone at at distance of 20m. (d) A helicopter at a distance of 500m. To compose the dataset, three different drones are used. 4. For the protection of people, animals and property which are unrelated to the flight, there must be a horizontal safety distance between these and the unmanned aircraft throughout the flight. THE UNIVERSITY OF SOUTHERN CALIFORNIA SPECIFICALLY DISCLAIMS ANY WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE OR NON-INFRINGEMENT. The computational part is done on a Dell Latitude 5401 laptop equipped with an Intel i7-9850H CPU and an Nvidia MX150 GPU. Notably, the Boson sensor of the FLIR Breach has a higher resolution than the one used in [11] where a FLIR Lepton sensor with 8060 pixels was used. The three drone types of the dataset. its variants. The captured data is from a thermal infrared camera (IRcam), a camera in the visible range (Vcam), and a microphone. The background sound class contains general background sounds recorded outdoor in the acquisition location and includes some clips of the sounds from the servos moving the pan/tilt platform where the sensors were mounted. Permission is hereby granted, free of charge, to any person obtaining a copy of the database and associated documentation files (the USC DRONE DATASET), to deal in the database without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, and/or sell copies of the USC DRONE DATASET, and to permit persons to whom the dataset is furnished to do so, provided that the above copyright notice(s) and this paragraph and the following two paragraphs appear in all copies of the USC DRONE DATASET and in supporting documentation. Beside, we have not found any previous study that addresses the detection task as a function of distance to the target. Due to its adjustable zoom lens, the field of view of the Vcam can be set to different values, which in this work is set to about the same field of view as the IRcam. Institution: School of Information Technology, Halmstad University. Visiting Scholars and Postdoctoral Fellows, Computer Vision and Scene Analysis Subgroup, Visual Quality and Perceptual Coding Subgroup, Biomedical and Information Processing Subgroup, Copyright 2013 USC Media Communications Lab. Occasionally occurring in the dataset are also the black kite (Milvus migrans) of the Accipitridae family and the Eurasian skylark (Alauda arvensis) of the lark family (Alaudidae). This dataset can be used for UAV-based human behavior understanding, including action recognition, pose estimation, re-identification, and attribute recognition. The annotations are in .mat-format and have been done using the Matlab video labeler. To track a small flying drone, we utilize the residual information between consecutive image frames. Guvenc I., Koohifar F., Singh S., Sichitiu M.L., Matolak D. Detection, tracking, and interdiction for amateur drones. Given that the drones must be flown within visual range due to regulations, the largest sensor-to-target distance for a drone in the dataset is 200m, and acquisitions are made in daylight. Dataset containing IR, visible and audio data that can be used to train and evaluate drone detection sensors and systems. The distribution of videos among the four output video classes is shown in Tables2 and and3.3. A Pololu Mini Maestro 12-Channel USB servo controller is included so that the respective position of the servos can be controlled from the laptop. (a) Hubsan H107D+. These drones differ in size, with Hubsan H107D+ being the smallest, with a side length from motor-to-motor of 0.1m. The Phantom 4 Pro and the DJI Flame Wheel F450 are slightly larger with 0.3 and 0.4m motor-to-motor side lengths, respectively. The provided data can help in developing systems that distinguish drones from other objects that can be mistaken for a drone, such as birds, airplanes or helicopters. Federal government websites often end in .gov or .mil. This outputs a 1024768 video stream in Mjpg-format at 30 FPS via a USB connector. Careers.

Example of IR video with two drones appearing in the image. The https:// ensures that you are connecting to the This table also contains information about the exact drone type and if the clip comes from the Internet or not. HHS Vulnerability Disclosure, Help This also facilitates transport and deployment outdoors, as shown in the right part of the figure. UAV-Human is a large dataset for human behavior understanding with UAVs. The Close distance bin is from 0m out to a distance where the target is 15 pixels wide in the IRcam image, i.e. Overall, the video dataset contains 650 videos (365 IR and 285 visible, of ten seconds each), with a total of 203328 annotated frames. The military scenario to this challenge is to improve capabilities to protect people and equipment against the threat of misuse of small (Class I) UAS such as hobby drones. The the requirement for recognition according to DRI. Peter LENK, NATO Communications and Information Agency, Vice-Chairs: Since the servos have shown a tendency to vibrate when holding the platform in specific directions, a third channel of the servo controller is also used to give the possibility to switch on and off the power to the servos using a small optoisolated relay board. The role of the fish-eye camera is not to detect specific classes but to detect moving objects in its field of view. Examples of varying weather conditions in the dataset. The version used in this work is an F450 quadcopter. The new PMC design is here! This is followed by a multi-object Kalman filter tracker, which, after calculating the position of the best-tracked target, sends the azimuth and elevation angles. Before It also includes other flying objects that can be mistakenly detected as drones, such as birds, airplanes or helicopters. The biggest challenge in adopting deep learning methods for drone detection is the limited amount of training drone images. A drone monitoring system that integrates deep-learning-based detection and tracking modules is proposed in this work. PMC legacy view The IR videos have a resolution of 320256 pixels, whereas the visible videos have 640512. Taha B., Shoufan A. The captured videos are recorded at locations in and around Halmstad and Falkenberg (Sweden), at Halmstad Airport (IATA code: HAD/ICAO code: ESMT), Gothenburg City Airport (GSE/ESGP) and Malm Airport (MMX/ESMS). sharing sensitive information, make sure youre on a federal The drone detection system used in this project utilized several sensors at the same time, including sensor fusion. To allow studies as a function of the sensor-to-target distance, the dataset is divided into three categories (Close, Medium, Distant) according to the industry-standard Detect, Recognize and Identify (DRI) requirements [7], built on the Johnson criteria [8]. 5. Real-Time Drone Detection and Tracking With Visible, Thermal and Acoustic Sensors". segmentation taqadam polygons FOIA What happens when a drone hits an airplane wing? "Svanstrm F, Alonso-Fernandez F and Englund C. (2021). The Medium bin stretches from where the target is from 15 down to 5 pixels, hence around the DRI detection point, and the Distant bin is beyond that. The annotation of the respective clips has the additional tag LABELS, e.g. In addition to using several different sensors, the number of classes is higher than in previous studies [4]. 1. The dataset contains 90 audio clips and 650 videos (365 IR and 285 visible). The output from the IRcam is sent to the laptop via a USB-C port at a rate of 60 frames per second (FPS). This dataset can be used to build a drone detection system, which can aid in preventing threatening situations where the security of people or facilities can be compromised, such as flying over restricted areas in airports or crowds in cities. If the detection system is to be placed, for example, on-board a drone, it must also be considered that it would affect battery duration, reducing the effective flying time of the drone. Due to the limited field of view of these cameras, they are steered towards specific directions guided by a fish-eye lens camera (Fcam) covering 180 horizontally and 90 vertically. Importing Matlab files into a Python environment can also be done using the scipy.io.loadmat command. Jrgen GROSCHE, Germany To achieve the pan/tilt motion, two Hitec HS-7955TG servos are used. Chair: The sensors are mounted on a pan/tilt platform Servocity DDT-560H direct drive. Further information is provided here. On average, these species have a wingspan of 0.8m, making them about twice the size of the medium-sized consumer grade drone. http://dx.doi.org/10.1109/ICPR48806.2021.9413241, https://www.infinitioptics.com/sites/default/files/attachments/Infiniti%20DRI%20Whitepaper.pdf, https://www.youtube.com/channel/UCx-PY5Q1Z5sJOQ9e8wvwvWQ. Audio labels: Drone, Helicopter and Background. 8 shows an image taken from the IRcam video stream. In some few cases, these vehicles fly at very low speed or are hovering. However, this detection was done manually by a person looking at the live video stream.

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