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Generalized optical flow in the scale space
Gong, Haifeng; Pan, Chunhong; Yang, Qing; Lu, Hanqing; Ma, Songde
Source PublicationCOMPUTER VISION AND IMAGE UNDERSTANDING
2007
Volume105Issue:1Pages:86-92
SubtypeArticle
AbstractScale space is a natural way to handle multi-scale problems. Yang and Ma have considered the correspondence between scales, and proposed optical flow in the scale space. In this paper, we generalized Yang and Ma's work to generic images. We first generalize the Horn-Schunck algorithm to multi-dimensional multi-channel image sequence. Since the global smoothness constraint for regularization is no longer suitable in general cases, we introduce localized smoothness regularization. In scale space optical flow, points in original image trends to aggregate at a large scale, so we introduce aggregation density as an additional smoothness coefficient. At last, we apply the proposed methods to color images and 3D images. (c) 2006 Elsevier Inc. All rights reserved.
KeywordScale Space Optical Flow Segmentation Filtering
WOS HeadingsScience & Technology ; Technology
WOS KeywordANISOTROPIC DIFFUSION ; EDGE-DETECTION
Indexed BySCI
Language英语
WOS Research AreaComputer Science ; Engineering
WOS SubjectComputer Science, Artificial Intelligence ; Engineering, Electrical & Electronic
WOS IDWOS:000243460900007
Citation statistics
Cited Times:3[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/9386
Collection09年以前成果
AffiliationChinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100080, Peoples R China
Recommended Citation
GB/T 7714
Gong, Haifeng,Pan, Chunhong,Yang, Qing,et al. Generalized optical flow in the scale space[J]. COMPUTER VISION AND IMAGE UNDERSTANDING,2007,105(1):86-92.
APA Gong, Haifeng,Pan, Chunhong,Yang, Qing,Lu, Hanqing,&Ma, Songde.(2007).Generalized optical flow in the scale space.COMPUTER VISION AND IMAGE UNDERSTANDING,105(1),86-92.
MLA Gong, Haifeng,et al."Generalized optical flow in the scale space".COMPUTER VISION AND IMAGE UNDERSTANDING 105.1(2007):86-92.
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