Vision-Based Collision Avoidance for Unmanned Aerial Vehicles by Recurrent Neural Networks
References:
[1] The website of the Taipei Traffic Control Center http://tms.bote.taipei.gov.tw/main.jsp?lang=zh_TW.
[2] “Unmanned Aircraft Systems". ICAO. Accessed 2nd August, 2016 http://www.icao.int/Meetings/UAS/Documents/Circular%20328_en.pdf.
[3] S. A. Cambone, K. J. Krieg, P. Pace and L. Wells II, “Unmanned aircraft systems (UAS) roadmap 2005–2030,” USA: Office of the Secretary of Defense, 2005.
[4] M. Corcoran, "Drone wars: The definition dogfight". Accessed 2nd August 2016. http://www.abc.net.au/news/2013-03-01/dronewars-the-definition-dogfight/4546598.
[5] A. Ahmed, M. Nagai, C. Tianen, and R. Shibasaki, “Uav based monitoring systemand object detection technique development for a disaster area,” International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, vol. 37, pp. 373–377, 2008.
[6] J. Polo, G. Hornero, C. Duijneveld, A. García and O. Casas, “Design of a low-cost Wireless Sensor Network with UAV mobile node for agricultural applications,” Computers and Electronics in Agriculture, vol. 119, pp. 19–32, 2015.
[7] B. Chen, Z. Chen, L. Deng, Y. Duan and J. Zhou, “Building change detection with RGB-D map generated from UAV images,” Neurocomputing, vol. 208, pp. 350–364, 2016.
[8] B. Coifman, M. McCord, R. Mishalani, M. Iswalt and Y. Ji, “Roadway trafficmonitoring froman unmanned aerial vehicle,” IEE Proceedings-Intelligent Transport Systems, vol. 153, no. 1, pp. 11–20, 2006.
[9] K. Kanistras, G. Martins, M. J. Rutherford and K. P. Valavanis, “Survey of unmanned aerial vehicles (uavs) for traffic monitoring,” in Handbook of Unmanned Aerial Vehicles, pp. 2643–2666, 2015.
[10] P. J. Hiltner, “Drones Are Coming: Use of Unmanned Aerial Vehicles for Police Surveillance and Its Fourth Amendment Implications,” The. Wake Forest JL & Pol'y, vol. 3, pp. 397, 2013.
[11] V. Reilly, H. Idrees and M. Shah, “Detection and tracking of large number of targets in wide area surveillance,” Computer Vision ECCV, pp. 186-199, 2010.
[12] Y. Wang, Z. Zhang and Y. Wang, “Moving Object Detection in Aerial Video”, 11th Inter-national Conference on Machine Learning and Applications, pp. 446-450, 2012.
[13] C. Lin, S. Pankanti, G. Ashour, D. Porat and J. R. Smith, “Moving camera analytics: Emerging scenarios, challenges, and applications”, IBM Journal of Research and Development, vol. 59, pp: 5:1-5:10, 2015.
[14] H. Zhou, H. Kong, L. Wei and D. Creighton, “Efficient Road Detection and Tracking for Unmanned Aerial Vehicle”, Transactions on Intelligent Transportation Systems, vol. 16, pp. 297-309, 2015.
[15] T. Moranduzzo and F. Melgani, “Automatic Car Counting Method for Unmanned Aerial Vehicle Images”, Geoscience and Remote Sensing, vol. 52, pp. 1635 – 1647, 2014.
[16] S. Parameswaran, C. Lane, B, Bagnall and H. Buck, “Marine Object Detection in UAV full-motion video”, Proc. SPIE 9076 Airborne Intelligence, surveillance, Reconnaissance Systems and Applications, XI, 907608, 2014.
[17] The website of ImageFusion.Org, The Online Resource for Research in Image Fusion, http://www.imagefusion.org/.
[18] The website of Flir camera, http://www.flir.tw/flirone/.
[19] The website of Softmax, http://ufldl.stanford.edu/tutorial/supervised/SoftmaxRegression/.
[20] Y. Lecun, L. Bottou, Y. Bengio and P. Haffner, “Gradient-based learning applied to document recognition”, Proceedings of the IEEE, vol. 86, no. 11, pp. 2278-2324, 1998.
[21] A. Mnih, and G. E. Hinton, “Learning nonlinear constraints with contrastive backpropagation,” In: Neural Networks, IJCNN'05. Proceedings. 2005 IEEE International Joint Conference on. IEEE, p. 1302-1307, 2005.
[22] R. Girshick, J. Donahue, T. Darrell, and J. Malik, “Region-based convolutional networks for accurate object detection and segmentation,” IEEE Transactions on Pattern Analysis & Machine Intelligence, vol. 38, no. 1, pp. 1–1, 2015.
[23] A. Graves, M. Liwicki, S. Fernandez, R. Bertolami, H. Bunke and J. Schmidhuber, “A Novel Connectionist System for Improved Unconstrained Handwriting Recognition.” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 31, no. 5, pp. 855–868, 2009.
[24] R. Girshick, “Fast r-cnn,” 2015 IEEE International Conference on Computer Vision (ICCV), 2015.
[25] S. Hochreiter and J. Schmidhuber, "Long short-term memory". Neural Computation. vol. 9, no. 8, pp. 1735–1780, 1997.
[26] G. E. Hinton, et al., “Deep Neural Networks for Acoustic Modeling in Speech Recognition,” IEEE Signal Processing Magazine, vol. 29, no. 6, pp. 82–97, 2012.
[27] The website of Mission Planner, http://ardupilot.org/planner/docs/mission-planner-overview.html.
[28] Y. Wu, J. Lim and M. H. Yang, “Online Object Tracking: A Benchmark,” In: 2013 IEEE Conference on Computer Vision and Pattern Recognition, pp. 2411-2418, 2013.
[29] Y. Wu, J. Lim and M. H. Yang, “Object tracking benchmark,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 37, no. 9, pp. 1834-1848, 2015.
[30] P. Liang, E. Blasch and H. Ling, “Encoding color information for visual tracking: Algorithms and benchmark,” IEEE Transactions on Image Processing, vol. 24, no. 12, pp. 5630-5644, 2015.
[31] A. W. M. Smeulders, D. M. Chu, R. Cucchiara, S. Calderara, A. Dehghan and M. Shah, “Visual tracking: An experimental survey,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 36, no. 7, pp. 1442-1468, 2014.
[32] M. Mueller, N. Smith and B. Ghanem, “A Benchmark and Simulator for UAV Tracking,” ECCV 2016: European Conference on Computer Vision, pp. 445-461, 2016.
[33] A. Anjos, and S. Marcel, “Counter-measures to photo attacks in face recognition: A public database and a baseline,” in Proc. IJCB, pp. 1–7, 2011.
[34] Wu, H.Y., M. Rubinstein, E. Shih, J. Guttag, F. Durand and W. Freeman, “Eulerian video magnification for revealing subtle changes in the world,” ACM Trans. Graph., vol. 31, no. 4, Art. ID 65, 2012.