SIFT(Scale Invariant Feature Transform)特征匹配算法是Lowe提出来的用于图像特征匹配的算法,是目前特征匹配领域的热点,对图像的旋转,尺度缩放和亮度变换保持不变,对视角变换,仿射变换保持一定程度的稳定。SIFT特征点是图像的一种尺度不变局部特征点,具有独特性好,信息量丰富,多量性,高速性,可扩展性等特点。该算法...
Self-calibration with two views using the scale-invariant feature transform [ A ]. Proceedings of the International Symposium on Visual Computing [ C ]. Springer Berlin/Heidelberg,2006:589 - 595.Yun J.-H., Park R.-H., « Self-Calibration with Two Views U...
SIFT3D is an analogue of the scale-invariant feature transform (SIFT) for three-dimensional images. It leverages volumetric data and real-world units to detect keypoints and extract a robust description of their content. It can also perform 3D image registration by matching SIFT3D features and ...
④scale invariant feature transform (SIFT):sparse SIFT包括scale space extrema searching, sub-pixel keypoint refining, dominant orientation assignment, featuredescription四步。 dense SIFT,PCA-SIFT,speed-up robust features (SURF) ⑤HOG:捕捉对象边缘或局部的形状信息。 bag-of-visual-words (BoVW) models ...
Feature-Guided Black-Box (FGBB)通过尺度不变特征变换(Scale Invariant Feature Transform),利用从图像中提取的特征来指导对抗性扰动的创建。高概率分配给影响人类视觉系统中图像构成的像素,而对抗示例的创建被视为一种双人游戏,其中第一个玩家最小化与对抗示例的距离,第二个玩家可以扮演不同的角色,从而最小化对抗示...
In this paper, we per- form an analysis of features with combinations of scale and rotation invariance in the bag-of-features framework. We have focused on the scale invariant feature transform (SIFT) to perform the analysis but other features such as speeded-up robust features (SURF) can ...
To account for these image-level variations, we employed the scale-invariant feature transform (SIFT) descriptor to capture expression patterns on local patches of ISH images [22, 23]. This approach can produce robust representations that are invariant to various distortions on the images. To ...
The handcrafted features are learned using descriptors such as histograms of oriented gradients (HOG), binarised statistical image features (BSIF), scale-invariant feature transform (SIFT), local binary pattern (LBP), Gabor Filter, speeded up robust feature (SURF). A handcrafted-based feature ...
The method first matches the Scale Invariant Feature Transform (SIFT) points using a modified matching technique between two frames extracted from a video clip and then localizes the scoreboard by computing a robust estimate of the matched point cloud in a two-stage non-scoreboard filter process ...
automatic feature extraction using algorithms such as Harris-Stephen operator, Forstner, Smallest Univalue Segment Assimilating Nucleus (SUSAN), Features from Accelerated Segment Test (FAST) operators [25] Scale-Invariant Feature Transform (SIFT) [24], Speeded Up Robust Feature (SURF) and similar [...