CASIA OpenIR  > 09年以前成果
Fast global motion estimation via iterative least-square method
Wang, J; Wang, HF; Liu, QS; Lu, HQ; Narayanan, PJ; Nayar, SK; Shum, HY
Source PublicationCOMPUTER VISION - ACCV 2006, PT II
AbstractThis 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 HeadingsScience & Technology ; Technology
Indexed ByISTP ; SCI
WOS Research AreaComputer Science
WOS SubjectComputer Science, Artificial Intelligence ; Computer Science, Theory & Methods
WOS IDWOS:000235773200035
Citation statistics
Document Type期刊论文
AffiliationChinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100080, Peoples R China
Recommended Citation
GB/T 7714
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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