Computer Vision Controlling an Autonomous Unmanned Aerial Vehicle Flight over a Railway

Author(s):  
Artem O. Lebedev ◽  
Vitaly V. Vasilev ◽  
Boris N. Novgorodov ◽  
Andrey G. Paulish
2021 ◽  
Author(s):  
Brendan Alvey ◽  
Derek T. Anderson ◽  
Andrew Buck ◽  
Matthew Deardorff ◽  
Grant Scott ◽  
...  

2020 ◽  
Author(s):  
Anil Mallidi ◽  
Sabah Mohammed

This is a research project which uses computer vision techniques to find out the empty parking spaces in any given Parking lot. It uses existing functions from OpenCV library in Python programming language to extract the parking lines from an image.


2020 ◽  
Author(s):  
Anil Mallidi ◽  
Sabah Mohammed

This is a research project which uses computer vision techniques to find out the empty parking spaces in any given Parking lot. It uses existing functions from OpenCV library in Python programming language to extract the parking lines from an image.


2020 ◽  
Vol 118 (5) ◽  
pp. 487-500 ◽  
Author(s):  
P Corey Green ◽  
Harold E Burkhart

Abstract Abstract An unmanned aircraft system was evaluated for its potential to capture imagery for use in plantation loblolly pine (Pinus taeda L.) regeneration surveys. Five stands located in the Virginia Piedmont were evaluated. Imagery was collected using a recreational grade unmanned aerial vehicle at three flight heights above ground with a camera capable of capturing red–green–blue imagery. Two computer vision approaches were evaluated for their potential to automatically detect seedlings. The results of the study indicated that the proposed methods were limited in capability of generating reliable counts of seedlings in the locations evaluated. In conditions with low numbers of natural seedlings and sufficiently large planted seedlings, the detection methods performed with higher levels of accuracy. Challenges including global positioning system errors and image distortion made comparisons between ground samples and imagery difficult. In summary, unmanned aircraft systems have potential for use in plantation pine regeneration surveys if the challenges encountered can be addressed. Study Implications: Following the establishment of a pine plantation, it is important to estimate survival and possible recruitment of natural conifers. As the popularity of unmanned aircraft systems (UAS) has increased, forest managers have begun to explore their use for resource assessment. This study investigated using imagery captured with a recreational grade UAS, in conjunction with automated computer vision counting techniques, for use in regeneration surveys. The results of this research indicate that significant challenges must be addressed before UAS can become an integral component of survival assessments. Aircraft constraints, legal restrictions, low image quality, and high levels of natural pine regeneration limited the success of the proposed methods. In selected cases, however, favorable conditions led to accurate detection. Additionally, UAS imagery has the potential for assessing other stand characteristics such as competing vegetation and drainage patterns. Going forward, UAS imagery and automated counting approaches have the potential to supplement, but not fully replace, ground regeneration surveys if the challenges encountered in this study can be addressed.


2020 ◽  
Vol 36 (1) ◽  
pp. 73-88 ◽  
Author(s):  
Yongding Tian ◽  
Cheng Zhang ◽  
Shang Jiang ◽  
Jian Zhang ◽  
Wenhui Duan

2014 ◽  
Vol 15 (3) ◽  
pp. 209-214 ◽  
Author(s):  
Alexey Y. Aksenov ◽  
Sergey V. Kuleshov ◽  
Alexandra A. Zaytseva

Abstract The paper considers an approach for application of computer vision systems to solve the problem of unmanned aerial vehicle control. The processing of images obtained through onboard camera is required for absolute positioning of aerial platform (automatic landing and take-off, hovering etc.) used image processing on-board camera. The proposed method combines the advantages of existing systems and gives the ability to perform hovering over a given point, the exact take-off and landing. The limitations of implemented methods are determined and the algorithm is proposed to combine them in order to improve the efficiency.


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