Shubha Bhat
Skip Abstract Section
Abstract
In this paper we discuss the key functional and quality attribute requirements and the associated design challenges in engineering a computer vision guided UAV (Unmanned Aerial Vehicle) system. The non-functional requirements of the UAV system as a wholeare identified and mapped to the computer vision subsystem which aids in the navigation process. Expectations on availability, reliability, performance, security and evolution of the vision subsystemare discussed and the related software design challenges elaborated
- Dr K C Wong, "Unmanned Aerial Vehicles (Uavs) -- Are They Ready This Time? Are We?", Royal Aeronautical Society, Sydney Branch, 26 Nov 1997.Google Scholar
- Bruce T Clough, "Unmanned Aerial Vehicles: Autonomous Control Challenges, A Researcher's Perspective", Air Force Research Laboratory, ControlScience Division, Chapter 3, CooperativeControl and Optimization, 35--53, Compiled Authors R Murphey and P M Paradalos (eds), Kluwer Academic Publishers, 2002.Google Scholar
- Shane Agostino, Matthew Mammone, Matthieu Nelson, Tong Zhou, "Classification of Unmanned Air Vehicles", Technical Academic Report, under the guidance of Dr Maziar Arjomandi, Aeronautical Engineering Department, University of Adelaide, Australia.Google Scholar
- Henri Eisenbeiss, "A Mini Unmanned Aerial Vehicle (UAV): System Overview and Image Acquisition", International Workshop on Processing and Visualization using high-resolution imagery, 18-20 Nov 2004, Pitsanulok, Thailand.Google Scholar
- M. Kontitsis, Kimon P Valavanis, N Tsourveloudis, "A UAV Vision System for Airborne Surveillance", Proceedings of the 2004 IEEE, International Conference on Robotics and Automation, New Orleans, LA, April 2004.Google Scholar
- Erdal Torun, "UAV Requirements and Design Considerations", paper presented at the RTO SCI Symposium on "Warfare Automation: Procedures and Techniques for Unmanned Vehicles", held in Ankara, Turkey, 26-28 April 1999 and published in RTO MP-44.Google Scholar
- Liu Jiufu, Yang Zhong, "UML and B method based analysis and refinement for flight control software of unmanned aerial vehicle", 2008 International Conference on Computer Science and Software Engineering. Google ScholarDigital Library
- Fei-Bin Hsiao*, Ying-Chih Lai, Hian-Kun Tenn, Sheng-Yen Hsieh, Chun-Chih Chen and Woei-Leong Chan, "The Development of an Unmanned Aerial Vehicle System with Surveillance, Watch, Autonomous Flight and Navigation Capability", appeared in 21st Bristol UAV systems Conference, April 2006.Google Scholar
- Krishnan Rangarajan, N Swaminathan, Vishnu Hegde, Jacob Jacob, "Product Quality Framework: A Vehicle for focusing on Product Quality Goals", ACM SIGSOFT, Software Engineering Notes vol 26 no 4 page 77, July 2001. Google ScholarDigital Library
- Ricardo C Bonfim Rodrigues and Sergio Roberto Pellegrino, "An Experimental Evaluation of Algorithms for Aerial Image Matching", 17th International Conference on Systems, Signals and Image Processing (IWSSIP), 2010.Google Scholar
- Luca Lucchese, "Estimating Affine Transformations In The Frequency Domain", Department of Electrical and Computer Engineering, University of California at Santa Barbara, 2001.Google Scholar
- Ali Shokoufandeh, Ivan Marsic, Sven J Dickinson, "Viewbased object recognition using saliency maps", Image and Vision Computing 17 (1999) 445--460.Google ScholarCross Ref
- Sven Dickinson, "Beyond One-to-One Feature Correspondence: The Need for Many-to-Many Matching and Image Abstraction", IEEE proceedings, 978-1-4244-3993-5/09, 2009.Google Scholar
- Nick Kingsbury, "Rotation-invariant local feature matching with complex wavelets", appeared in European Signal Processing Conference, 2006.Google Scholar
- Chris Constantinides, Paul Parkinson, "Security Challenges in UAV development", 27th Digital Avionics Systems Conference, Oct 26-30, 2008.Google Scholar
- Ben Ludington, Eric Johnson and George Vachtsevanos, "Augmenting UAV Autonomy: Vision-Based Navigation and Target Tracking for Unmanned Aerial Vehicles", IEEE Robotics and Automation Magazine, 1070-9932/06, Sep 2006.Google Scholar
- Nathan Funk, " A Study of the Kalman Filter applied to Visual Tracking", University of Alberta, Project for CMPUT 652, Dec 2003.Google Scholar
- Ben Ludington, Eric Johnson and George Vachtsevanos, "Augmenting UAV Autonomy: Vision-Based Navigation and Target Tracking for Unmanned Aerial Vehicles", IEEE Robotics and Automation Magazine, 1070-9932/06, Sep 2006.Google Scholar
- Nathan Funk, "A Study of the Kalman Filter applied to Visual Tracking", Univ of Alberta, Project for CMPUT 652, Dec 2003.Google Scholar
- Fredrik Gustafsson, Fredrik Gunnarsson, Niclas Bergman, Urban Forssell, Particle Filters for Positioning, Navigation, and Tracking, IEEE Transaction on Signal Processing, vol. 50, No. 2, February 2002. Google ScholarDigital Library
- Peter Kovesi, "Image Features from Phase Congruency", Department of Computer Science, the University of Western Australia, Nedlands, W.A. 6907, 1999.Google Scholar
- Nick Kingsbury, "Multiscale Keypoint Detection Using the Dual-Tree Complex Wavelet Transform", ICIP 2006: 1625--1628, 2006.Google Scholar
- Nick Kingsbury, "Rotation-invariant local feature matching with complex wavelets", appeared in European Signal Processing Conference, 2006.Google Scholar
- Alper Yilmaz, Omar Javed, Mubarak Shah, "Object Tracking: A Survey", ACM Computing Surveys, Vol.38, No 4, Article 13, Dec 2006. Google ScholarDigital Library
- Kaiming He, Jian Sun, Xiaoou Tang, "Single Image Haze Removal Using Dark Channel Prior", appeared in CVPR, 2009.Google Scholar
- David G Lowe, "Object Recognition from Local Scale Invariant Features", In Proc of the International Conference on Computer Vision, Corfu, September 1999. Google ScholarDigital Library
- R.R. Coifman and D.L. Donoho, "Translation-invariant denoising," in Wavelets and Statistics, A. Antoniadis, Ed. New York: Springer-Verlag, 1995.Google Scholar
- M. Lang, H. Guo, J.E. Odegard, C.S. Burrus, and R.O. Wells, Jr., "Noise reduction using an undecimated discrete wavelet transform," IEEE Signal Processing Lett., vol. 3, no. 1, pp. 10--12, Jan. 1996.Google ScholarCross Ref
- J. D. B. Nelson, S. K. Pang, N. G. Kingsbury, and S. J. Godsill, "Tracking Ground Based Targets in Aerial Video with Dual- Tree Wavelet Polar Matching and Particle Filtering, Appeared IEEE proceedings, 2008.Google Scholar
- Tao Yang et al, "Real-time multiple objects tracking with occlusions handling in dynamic scenes", proceedings of IEEE computer society conference on CVPR, 2005. Google ScholarDigital Library
Recommendations
A Computer Vision System for Guidance of VTOL UAVs Autonomous Landing
BRACIS '15: Proceedings of the 2015 Brazilian Conference on Intelligent Systems (BRACIS)Nowadays, research has been developed in order to increase the autonomy of Unmanned Aerial Vehicles (UAVs). The procedure of autonomy increase consists of transferring part of the decision-making process of the human UAV operators for the vehicle ...
Real-Time Embedded Computer Vision on UAVs:: UAVision2020 Workshop Summary
Computer Vision – ECCV 2020 WorkshopsAbstractIn this paper we present an overview of the contributed work presented at the UAVision2020 (International workshop on Computer Vision for UAVs) ECCV workshop. Note that during ECCV2020 this workshop was merged with the VisDrone2020 workshop. This ...
A Vision-Based Automatic Landing Method for Fixed-Wing UAVs
In this paper, a vision-based landing system for small-size fixed-wing unmanned aerial vehicles (UAVs) is presented. Since a single GPS without a differential correction typically provide position accuracy of at most a few meters, an airplane equipped ...
Comments