Development of a Peripheral–Central Vision System for Small Unmanned Aircraft Tracking

2021 ◽  
pp. 1-14
Author(s):  
Changkoo Kang ◽  
Haseeb Chaudhry ◽  
Craig A. Woolsey ◽  
Kevin Kochersberger
Keyword(s):  
Vision System ◽  
Unmanned Aircraft ◽  
Central Vision ◽  
Aircraft Tracking

scholarly journals DETECTION AND TRACKING OF MOVING OBJECTS WITH REAL-TIME ONBOARD VISION SYSTEM

2017 ◽  
Vol XLII-2/W4 ◽  
pp. 67-71 ◽  
Author(s):  
D. Y. Erokhin ◽  
A. B. Feldman ◽  
S. E. Korepanov
Keyword(s):  
Computer Vision ◽  
Real Time ◽  
Video Sequence ◽  
Moving Objects ◽  
Vision System ◽  
Unmanned Aircraft ◽  
Computer Vision System ◽  
Geometric Transformations ◽  
Detection And Tracking ◽  
Video Sensor

Detection of moving objects in video sequence received from moving video sensor is a one of the most important problem in computer vision. The main purpose of this work is developing set of algorithms, which can detect and track moving objects in real time computer vision system. This set includes three main parts: the algorithm for estimation and compensation of geometric transformations of images, an algorithm for detection of moving objects, an algorithm to tracking of the detected objects and prediction their position. The results can be claimed to create onboard vision systems of aircraft, including those relating to small and unmanned aircraft.

scholarly journals Onboard Visual Horizon Detection for Unmanned Aerial Systems with Programmable Logic

Electronics ◽  
2020 ◽  
Vol 9 (4) ◽  
pp. 614 ◽  
Author(s):  
Antal Hiba ◽  
Levente Márk Sántha ◽  
Tamás Zsedrovits ◽  
Levente Hajder ◽  
Akos Zarandy
Keyword(s):  
Vision System ◽  
Computational Cost ◽  
Detection Algorithm ◽  
Initial Guess ◽  
Unmanned Aircraft ◽  
Unmanned Aerial Systems ◽  
Single Shot ◽  
Camera Model ◽  
Radial Distortion ◽  
Horizon Detection

We introduce and analyze a fast horizon detection algorithm with native radial distortion handling and its implementation on a low power field programmable gate array (FPGA) development board in this paper. The algorithm is suited for visual applications in an airborne environment, that is on board a small unmanned aircraft. The algorithm was designed to have low complexity because of the power consumption requirements. To keep the computational cost low, an initial guess for the horizon is used, which is provided by the attitude heading reference system of the aircraft. The camera model takes radial distortions into account, which is necessary for a wide-angle lens used in most applications. This paper presents formulae for distorted horizon lines and a gradient sampling-based resolution-independent single shot algorithm for finding a horizon with radial distortion without undistortion of the complete image. The implemented algorithm is part of our visual sense-and-avoid system, where it is used for the sky-ground separation, and the performance of the algorithm is tested on real flight data. The FPGA implementation of the horizon detection method makes it possible to add this efficient module to any FPGA-based vision system.

Development of a Peripheral-Central Vision System for Small UAS Tracking

2019 ◽  
Author(s):  
Changkoo Kang ◽  
Haseeb Chaudhry ◽  
Craig A. Woolsey ◽  
Kevin B. Kochersberger
Keyword(s):  
Vision System ◽  
Central Vision

Team OSAM-UAV’s Design for the 2008 AUVSI Student UAS Competition

2009 ◽  
Author(s):  
Christopher J. Hall ◽  
Daniel Morgan ◽  
Austin Jensen ◽  
Haiyang Chao ◽  
Calvin Coopmans ◽  
...  
Keyword(s):  
Open Source ◽  
Real Time ◽  
Flight Control ◽  
Autonomous Navigation ◽  
Delta Wing ◽  
Target Recognition ◽  
Vision System ◽  
Unmanned Aircraft ◽  
Measurement Unit ◽  
Ground Control

This paper, was originally prepared for and presented at the 2008 AUVSI Student UAS Competition, it provides the OSAM-UAV (Open-Source Autonomous Multiple Unmanned Aerial Vehicle) team’s design of an unmanned aircraft system for remote target recognition missions. Our OSAM-UAVs are designed to be small in size with strong airframes, and low-cost using open-source in both autopilot hardware and flight control software. A robust EPP-based delta wing airframe is used to prevent damage to the airframe during landing or even crashes. Autonomous navigation is achieved using an open-source Paparazzi autopilot, which gives special attention to safety during operation. Our system has been further enhanced by using the Xbow MNAV Inertial Measurement Unit (IMU) in place of the Paparazzi’s standard infrared (IR) sensors, for better georeferencing. An array of light-weight video cameras have been embedded in the airframe, which stream video to the ground control station through wireless transmitters in real-time. The ground control system includes a computer vision system, which processes and geo-references images in real-time for target recognition. Experimental results show the successful autonomous waypoint navigation and real-time image processing.

COLOR PERCEPTION OF SMALL STIMULI WITH CENTRAL VISION. (Rep. No. 257).

1954 ◽  
Author(s):  
Beverly Hillmann ◽  
Katherine Connolly ◽  
Dean Farnsworth
Keyword(s):  
Color Perception ◽  
Central Vision

A closed-loop, ACT-R approach to modeling approach and landing with and without synthetic vision system (SVS) technology

2004 ◽  
Author(s):  
Michael D. Byrne ◽  
Alex Kirlik ◽  
Michael D. Fleetwood ◽  
David G. Huss ◽  
Alex Kosorukoff ◽  
...  
Keyword(s):  
Closed Loop ◽  
Vision System ◽  
Modeling Approach ◽  
Synthetic Vision

SVM-based global vision system of sports competition and action recognition

2020 ◽  
pp. 1-12
Author(s):  
Changxin Sun ◽  
Di Ma
Keyword(s):  
Target Recognition ◽  
Vision System ◽  
Task Assignment ◽  
Recognition Algorithm ◽  
Control Factor ◽  
Training Time ◽  
Adaboost Algorithm ◽  
Advantages And Disadvantages ◽  
Time Control ◽  
Correlation Degree

In the research of intelligent sports vision systems, the stability and accuracy of vision system target recognition, the reasonable effectiveness of task assignment, and the advantages and disadvantages of path planning are the key factors for the vision system to successfully perform tasks. Aiming at the problem of target recognition errors caused by uneven brightness and mutations in sports competition, a dynamic template mechanism is proposed. In the target recognition algorithm, the correlation degree of data feature changes is fully considered, and the time control factor is introduced when using SVM for classification,At the same time, this study uses an unsupervised clustering method to design a classification strategy to achieve rapid target discrimination when the environmental brightness changes, which improves the accuracy of recognition. In addition, the Adaboost algorithm is selected as the machine learning method, and the algorithm is optimized from the aspects of fast feature selection and double threshold decision, which effectively improves the training time of the classifier. Finally, for complex human poses and partially occluded human targets, this paper proposes to express the entire human body through multiple parts. The experimental results show that this method can be used to detect sports players with multiple poses and partial occlusions in complex backgrounds and provides an effective technical means for detecting sports competition action characteristics in complex backgrounds.

Modern Technology for Image processing and Computer vision -A Review

2018 ◽  
Vol 1 (2) ◽  
pp. 17-23
Author(s):  
Takialddin Al Smadi
Keyword(s):  
Image Processing ◽  
Computer Vision ◽  
Augmented Reality ◽  
Video Compression ◽  
Video Processing ◽  
Vision System ◽  
Citrus Fruit ◽  
Modern Technology ◽  
Image And Video Processing ◽  
Depth Video

This survey outlines the use of computer vision in Image and video processing in multidisciplinary applications; either in academia or industry, which are active in this field.The scope of this paper covers the theoretical and practical aspects in image and video processing in addition of computer vision, from essential research to evolution of application.In this paper a various subjects of image processing and computer vision will be demonstrated ,these subjects are spanned from the evolution of mobile augmented reality (MAR) applications, to augmented reality under 3D modeling and real time depth imaging, video processing algorithms will be discussed to get higher depth video compression, beside that in the field of mobile platform an automatic computer vision system for citrus fruit has been implemented ,where the Bayesian classification with Boundary Growing to detect the text in the video scene. Also the paper illustrates the usability of the handed interactive method to the portable projector based on augmented reality.   © 2018 JASET, International Scholars and Researchers Association

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