Adaptive Threshold Video Splicing Algorithm Based on Distance Feature
CHEN Xia-Yan1,2,WU Xian-Da1
1.Intelligent Detection Laboratory,Hefei Institute of Intelligent Machines,Chinese Academy of Sciences,Hefei 230031 2.Department of Automation,University of Science and Technology of China,Hefei 230027
Abstract An adaptive threshold video splicing algorithm based on distance feature is proposed to solve the problem of video splicing in virtual walkthrough system. The algorithm is used to splice video images captured by virtual walkthrough system.By extracting distance feature, the adaptive threshold sequential similarity detection algorithms (SSDA) it used to search the matching feature in the frame images to be matched. Then, the beginning column of the overlapping part it estimated. Experimental results show the proposed algorithm realizes video splicing better, reduces workload and accelerates the splicing speed.
[1] Lowe D G. Object Recognition from Local Scale Invariant Features // Proc of the 7th IEEE International Conference on Computer Vision. Kerkyra, Greece, 1999, Ⅱ: 1150-1157 [2] Lowe D G. Distinctive Image Features from Scale Invariant Key-Points. International Journal of Computer Vision, 2004, 60(2): 91-110 [3] Lei Zhongfeng. Video Stitching and Its Application to Visual Network Shopping. Master Dissertation. Beijing, China: Beijing University of Technology. College of Computer, 2004 (in Chinese) (雷中锋.视频拼接及在可视化网上购物中的应用.硕士学位论文.北京:北京工业大学.计算机学院, 2004) [4] Xie Lu, Liao Qingmin. Video Stitching of Diving Movement. Video Engineering, 2005, 278(8): 122-124 (in Chinese) (谢 路,廖庆敏.跳水动作视频拼接.电视技术, 2005, 278(8): 122-124) [5] Cheng Yunpeng. Matix. 2nd Edition. Xian, China: Northwestern Polytechnical University Press, 2000 (in Chinese) (程云鹏.矩阵论.第2版.西安:西北工业大学出版社, 2000) [6] Ma Lingkun, Zhang Zhenqiang. The Algorithmic Study of Image Overlap Region Patching Up. Control and Automation, 2007, 23(6): 310-312 (in Chinese) (马令坤,张震强.图像拼接算法的研究.微计算机信息, 2007, 23(6): 310-312) [7] Jing Qicheng, Jiao Shulan, Yu Bailin, et al. Chromatics. Beijing, China: Science Press, 1979 (in Chinese) (荆其诚,焦书兰,喻柏林,等.色度学.北京:科学出版社, 1979) [8] Barnea D I, Silverman H F. A Class of Algorithm for Fast Digital Image Registration. IEEE Trans on Computing, 1972, 21(2): 176-186 [9] Hong Zhenhua, Zhu Peiying. An Improved SSDA Applied in Target Tracking // Proc of the 9th IEEE International Conference on Pattern Recognition. Rome, Italy, 1988, Ⅱ: 767-769 [10] Hatabu A, Miyazaki T, Kuroda I. Optimization of Decision-Timing for Early Termination of SSDA-Based Block Matching // Proc of the IEEE International Conference on Acoustics, Speech and Signal Processing. Baltimore, USA, 2003: 821-824 [11] Castleman K R. Digital Image Processing. Upper Saddle River, USA: Prentice Hall, 1995 [12] Ban Xiaojuan, Ning Shurong, Zhang Ya, et al. Video Splicing Algorithm Based on Improved Adapted Threshold SSDA-In Traffic Scene Research and Application. Journal of System Simulation, 2008, 20(22): 6201-6204 (in Chinese) (班晓娟,宁淑荣,张 亚,等.一种改进的自适应阈值SSDA的视频拼接算法——在交通场景中的研究与应用.系统仿真学报, 2008, 20(22): 6201-6204)
2010, Vol. 23 
