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Fast global motion estimation via iterative least-square method
Wang, J; Wang, HF; Liu, QS; Lu, HQ; Narayanan, PJ; Nayar, SK; Shum, HY
2006
发表期刊COMPUTER VISION - ACCV 2006, PT II
卷号3852页码:343-352
文章类型Article
摘要This paper presents a Fast algorithm for global motion estimation based on Iterative Least-Square Estimation (ILSE) technique. Compared with the traditional framework, three improvements were made to accelerate the computation progress. First, a new 3-parameter linear model, together with its solution using modified ILSE method, is proposed to describe and estimate global motion, which is simple and reasonable. Second, a pre-analysis method, Gradient Thresholding (GT) method, is introduced to pre-analyze the image macro-blocks before global motion estimation using their gradient information, which reduce the computational cost by reducing the amount of involved blocks. Lastly, Successive Elimination Algorithm (SEA), which is used to calculate motion field, is improved by a now presented matching criterion considering both the gradient information and the intensity information. The presented method has been tested on a variety of image sequences, and experimental results illustrate its promising performance.
WOS标题词Science & Technology ; Technology
关键词[WOS]SUCCESSIVE ELIMINATION ALGORITHM
收录类别ISTP ; SCI
语种英语
WOS研究方向Computer Science
WOS类目Computer Science, Artificial Intelligence ; Computer Science, Theory & Methods
WOS记录号WOS:000235773200035
引用统计
文献类型期刊论文
条目标识符http://ir.ia.ac.cn/handle/173211/9272
专题09年以前成果
作者单位Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100080, Peoples R China
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Wang, J,Wang, HF,Liu, QS,et al. Fast global motion estimation via iterative least-square method[J]. COMPUTER VISION - ACCV 2006, PT II,2006,3852:343-352.
APA Wang, J.,Wang, HF.,Liu, QS.,Lu, HQ.,Narayanan, PJ.,...&Shum, HY.(2006).Fast global motion estimation via iterative least-square method.COMPUTER VISION - ACCV 2006, PT II,3852,343-352.
MLA Wang, J,et al."Fast global motion estimation via iterative least-square method".COMPUTER VISION - ACCV 2006, PT II 3852(2006):343-352.
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