航拍视频帧间快速配准算法
收稿日期: 2012-07-17
修回日期: 2012-10-10
网络出版日期: 2012-12-07
基金资助
国家自然科学基金(61005028,61175032,61005067,61101222);中国科学院知识创新工程(YYYJ-1122)
Fast Interframe Registration Method in Aerial Videos
Received date: 2012-07-17
Revised date: 2012-10-10
Online published: 2012-12-07
Supported by
National Natural Science Foundation of China (61005028, 61175032, 61005067, 61101222); Knowledge Innovation Project of Chinese Academy of Sciences(YYYJ-1122)
申浩 , 李书晓 , 申意萍 , 朱承飞 , 常红星 . 航拍视频帧间快速配准算法[J]. 航空学报, 2013 , 34(6) : 1405 -1413 . DOI: 10.7527/S1000-6893.2013.0239
To deal with the effect which is caused by camera moving, a fast and reliable image registration method between sequential frames for unmanned aerial vehicle (UAV) videos is proposed. Firstly, the stable FAST corners are selected via the constraints of spatial displacements and cornerness measurements. Meanwhile, an adaptive threshold method is involved in the feature detection process to improve environmental adaptability. Then, the binary descriptions of the detected features are generated by using the uncorrelated sample point set, which is obtained by training, and the matched points are established using the NN (Nearest Neighbor) algorithm based on hamming distances. Finally, the affine transformation parameters between adjacent frames are estimated using the matched points by RANSAC, which can be provided for further processing, such as moving object detection and tracking. Experimental results show that the proposed algorithm is fast and reliable, it has high environmental adaptability, and thus can meet the image registration requirements in UAV systems.
[1] Zitova B, Flusser J. Image registration methods: a survey. Image and Vision Computing, 2003, 21(11): 977-1000.
[2] Brown M, Lowe D. Automatic panoramic image stitching using invariant features. International Journal of Computer Vision, 2007, 74(1): 59-73.
[3] Wang Y L, Zhang X, Gao C,et al. Feature matching based global motion estimation in aerial video mosaicing. Acta Aeronautica et Astronautica Sinica, 2008, 29(5): 1218-1225. (in Chinese) 王云丽, 张鑫, 高超, 等. 航拍视频拼图中基于特征匹配的全局运动估计方法. 航空学报, 2008, 29(5): 1218-1225.
[4] Xu D, An J W. Global motion estimation by fitting optical flow in aerial video imagery. Acta Aeronautica et Astronautica Sinica, 2006, 27(1): 94-97. (in Chinese) 许东, 安锦文. 一种基于光流拟和的航拍视频图像全局运动估算方法. 航空学报, 2006, 27(1): 94-97.
[5] Battiato S, Bruna A R, Puglisi G. A robust block-based image/video registration approach for mobile imaging devices. IEEE Transactions on Multimedia, 2010, 12(7): 622-635.
[6] Lowe D G. Distinctive image features from scale-invariant keypoints. International Journal of Computer Vision, 2004, 60(1): 91-110.
[7] Steedly D, Pal C, Szeliski R. Efficiently registering video into panoramic mosaic. Proceedings of the 10th IEEE International Conference on Computer Vision, 2005: 1300-1307.
[8] Bay H, Tuytelaars T, Gool L V. Surf: speeded up robust features. Proceedings of the 9th European Conference on Computer Vision. Graz, Austria: 2006: 404-417.
[9] Rublee E, Rabaud V, Konolige K, et al. Orb: an efficient alternative to sift or surf. Proceedings of the 13th IEEE International Conference on Computer Vision, 2011: 2564-2571.
[10] Rosten E, Drummond T. Machine learning for high-speed corner detection. Proceedings of the 9th European Conference on Computer Vision. Graz, Austria: Springer-Verlag Berlin Heidelberg, 2006: 430-443.
[11] Viola P, Jones M. Rapid object detection using a boosted cascade of simple features. Proceedings of the 2001 IEEE Conference on Computer Vision and Pattern Recognition, 2001: 511-518.
[12] Calonder M, Lepetit V, Fua P. Brief: binary robust independent elementary features. Proceedings of the 11th European Conference on Computer Vision. Crete, Greece: Springer-Verlag Berlin Heidelberg, 2010: 778-792.
[13] Leutenegger S, Chli M, Siegwart R Y. BRISK: binary robust invariant scalable keypoints. Proceedings of the 13th IEEE International Conference on Computer Vision, 2011: 2548-2555.
[14] Fan B, Wu F, Hu Z. Aggregating gradient distributions into intensity orders: a novel local image descriptor. Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition, 2011: 2377-2384.
[15] Fischler M, Bolles R. Random sample consensus: a paradigm for model fitting with application to image analysis and automated cartography. Communications of the ACM, 1981, 24: 381-395.
[16] Hess R. Open SIFT. (2010-12-07). http://blogs.oregonstate.eduhess/code/sift/.
[17] Microsoft Corporation. Image composite editor. (2011-05-26)[2012-07-17]. http://research.microsoft.com/en-us/um/redmond/groups/ivm/ice/.
[18] ArcSoft Corporation. Panorama maker 6.[2012-07-17]. http://www.arcsoft.com/panorama-maker/.
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