Description: ExtractSURF
Extracts Speeded Up Robust Features from image. downlæ oad and install opencv 1.1pre-ExtractSURF
Extracts Speeded Up Robust Features from image. downlæ oad and install opencv 1.1pre
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Author:rahman |
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Description: Speeded Up Robust Features 在SIFT特正点匹配算法上进行改进，代码已完成Matlab->VC的程序打包-Speeded Up Robust Features in the SIFT matching algorithm special on-time improvement, the code has been completed Matlab-> VC packing process Platform: |
Size: 1154048 |
Author:萧峙清 |
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Description: In this paper, a novel scale- and rotation-invariant interest point detector and descriptor, coined SURF (Speeded Up Robust
Features) is presented. It approximates or even outperforms previously proposed
schemes with respect to repeatability, distinctiveness, and robustness, yet
can be computed and compared much faster.
This is achieved by relying on integral images for image convolutions by building on the strengths of the leading existing detectors and descriptors (in casu, using a Hessian matrix-based measure for the detector, and a
distribution-based descriptor) and by simplifying these methods to the
essential. This leads to a combination of novel detection, description, and
matching steps. The paper presents experimental results on a standard
evaluation set, as well as on imagery obtained in the context of a real-life
object recognition application. Both show SURF’s strong performance.-In this paper, a novel scale- and rotation-invariant interest point detector and descriptor, coined SURF (Speeded Up Robust
Features) is presented. It approximates or even outperforms previously proposed
schemes with respect to repeatability, distinctiveness, and robustness, yet
can be computed and compared much faster.
This is achieved by relying on integral images for image convolutions by building on the strengths of the leading existing detectors and descriptors (in casu, using a Hessian matrix-based measure for the detector, and a
distribution-based descriptor) and by simplifying these methods to the
essential. This leads to a combination of novel detection, description, and
matching steps. The paper presents experimental results on a standard
evaluation set, as well as on imagery obtained in the context of a real-life
object recognition application. Both show SURF’s strong performance. Platform: |
Size: 686080 |
Author:yangwei |
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Description: GPU Accelerating Speeded-Up Robust Features. Many computer vision tasks require interest point detection and description, such as real-time visual navigation. We present a GPU implementation of the recently proposed Speeded-Up Robust Feature extractor, currently the state of the art for
this task. Robust feature descriptors can give vast improvements
in the quality and speed of subsequent steps, but require intensive
computation up front that is well-suited to inexpensive graphics
hardware. We describe the algorithm’s translation to the GPU in
detail, with several novel optimizations, including a new method
of computing multi-dimensional parallel prefix sums. It operates
at over 30 Hz at HD resolutions with thousands of features and
in excess of 70 Hz at SD resolutions. Platform: |
Size: 1541120 |
Author:yangwei |
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Description: SURF算法，是SIFT的升级版，速度更快，性能也不差，快速实现图像特征点的检测和匹配。-SURF algorithm, is an upgraded version of SIFT, faster, not bad performance, rapid detection of image feature points and matching. Platform: |
Size: 1362944 |
Author:张东兴 |
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Description: This article presents a novel scale- and rotation-invariant detector and descriptor, coined SURF (Speeded-Up Robust Features).
SURF approximates or even outperforms previously proposed schemes with respect to repeatability, distinctiveness, and robustness,
yet can be computed and compared much faster.-This article presents a novel scale-and rotation-invariant detector and descriptor, coined SURF (Speeded-Up Robust Features). SURF approximates or even outperforms previously proposed schemes with respect to repeatability, distinctiveness, and robustness, yet can be computed and compared much faster. Platform: |
Size: 2754560 |
Author:xukaijun |
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Description: C++ implementation of performant scale- and rotation-invariant interest point detector and descriptor SURF: Speeded Up Robust Features Platform: |
Size: 104448 |
Author:Athos |
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Description: SURF算法作为一种新近出现的特征提取方法，在重复度、独特性、鲁棒性3个方面，均超越或接近以往提出的同类方法，并在计算效率上具有明显的优势。本代码采用SURF算法检测图像并进行坐标变换与图像拼接。
采用SURF算法对图像进行检测，其主要是用Hessian矩阵对图像进行检测，对图像的特征提取之后找到图像的特征点。之后采用最近临快速匹配（NN）、随机抽样一致性（RANSAC）算法和最小二乘法参数优化（LM）对特征点进行提纯匹配。最后在两幅图像中进行坐标变换，达到统一坐标系和图像拼接的效果。
-SURF（Speeded Up Robust Features） as a method of feature extraction which newly appeared is over or nearly previous method on duplication, uniqueness, and robustness and have a clear advantage on computational efficiency. This code uses the SURF and coordinate transformation algorithm to detect image and image matching.
This code uses the SURF algorithm of image detection, the main is to use the Hessian matrix of image for testing, to find the image after image feature extraction of feature points. After we used Nearest Neighbor (NN), Random Sample Consensus (RANSAC) algorithm and least square parameter optimization for purification of matching feature points. Coordinate transformation in the last two images, to coordinate system to achieve the same image stitching.
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Size: 2070528 |
Author:马丁 |
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Description: This function OPENSURF, is an implementation of SURF (Speeded Up Robust
Features). SURF will detect landmark points in an image, and describe
the points by a vector which is robust against (a little bit) rotation
,scaling and noise. It can be used in the same way as SIFT (Scale-invariant
feature transform) which is patented. Thus to align (register) two
or more images based on corresponding points, or make 3D reconstructions.- This function OPENSURF, is an implementation of SURF (Speeded Up Robust
Features). SURF will detect landmark points in an image, and describe
the points by a vector which is robust against (a little bit) rotation
,scaling and noise. It can be used in the same way as SIFT (Scale-invariant
feature transform) which is patented. Thus to align (register) two
or more images based on corresponding points, or make 3D reconstructions. Platform: |
Size: 1792000 |
Author:deokman |
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Description: Speeded Up Robust Features (SURF) SURF (Speeded Up Robust Features) is a robust local feature detector invariant to scale rotation and illumination similaire to SIFT Scale Invariant Feature Transform Platform: |
Size: 788480 |
Author:ghoualmi |
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Description: This code is an implementation of SURF (Speeded Up Robust Features). SURF will detect landmark points in an image, and describe the points by a vector which is robust against (a little bit) rotation,scaling and noise. It can be used in the same way as SIFT (Scale-invariant feature transform) which is patented. Thus to align (register) two or more images based on corresponding points. Platform: |
Size: 721920 |
Author:abdouninaceur |
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Description: 基于SURF的光流法的运动物体检测应用——检测PTZ是否转动
内容：
（1） 对光流法和SURF进行理论分析。
（2） 应用光流法对运动物体进行检测，理解David Stavens的demo。
（3） 用SURF提取的特征点来作为光流法中的特征点，来检测运动物体，并应用于一个实例：检测ptz云台是否转动。
【实验室项目】-use of optical flow with SURF
Motion estimation and video compression have developed as a major aspect of optical flow research, while the SURF (Speeded Up Robust Features) is a robust local and good feature detector. My task is to use SURF to replace the features of optical flow , and have a comparison of performance. Platform: |
Size: 7522304 |
Author:王松 |
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