OTHER
Distinctive Image Features from Scale-Invariant Keypoints
Matthijs C. Dorst
- 发表年份
- 2011
- 引用次数
- 13
摘要
The Scale-Invariant Feature Transform (or SIFT) algorithm is a highly robust method to extract and consequently match distinctive invariant features from images. These features can then be used to reliably match objects in diering images. The algorithm was rst proposed by Lowe [12] and further developed to increase performance resulting in the classic paper [13] that served as foundation for SIFT which has played an important role in robotic and machine vision in the past decade.
关键词
Scale-invariant feature transformArtificial intelligenceComputer visionInvariant (physics)Scale invariancePattern recognition (psychology)Computer scienceMathematicsImage (mathematics)Statistics
相关论文
OTHER
📊 26,957 引用
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
PERCEPTION
📊 22,245 引用
Artificial intelligence: a modern approach
1995
OTHER
开放获取📊 20,501 引用
Fractional Differential Equations
Igor Podlubný
2025
OTHER
📊 18,993 引用
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991