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extract_features2.tar
- 各种图像描述符算法,图像特征提取用的是SIFT特征检测子-computes steerable filters, SIFT descr iptor, moments, differential invariants, complex filters, shape context, spin images, PCA-SIFT.
object-tracking-based-on-TOD
- 基于纹理和边缘方向特征融合的目标跟踪程序代码，是基于mean shift框架的-This paper proposes a powerful and robust local descr iptor,called textureorientation descr iptor(TOD). TOD consists of two components: texture and orientation. Considering that the human shape shows more s
ShapeContext
- 全局形状特征描述符的形状上下文描述符的具体实现过程详细说明和实现代码-Global shape feature descr iptor shape context descr iptor detailed descr iption of the specific implementation process and the implementation code
fourier_descriptor
- Fourier descr iptor example on different shapes.Can reconstruct shape with few coeffecients
affintpoints
- 仿射不变Harris, Laplacian, det(Hessian) and Ridge 特征点检测 参考文献：An affine invariant interest point detector , K.Mikolajczyk and C.Schmid, ECCV 02, pp.I:128-142.-Matlab code for detecting Affine spatial interest points. Includes Harris, Laplacian, det(Hess
Human-Activity-Recognition
- In this programe, a four-dimensional spatiotemporal shape context descr iptor is introduced and used for human activity recognition in video
one
- 基于叶片数字图像的植物识别是自动植物分类研究的热点。但是随着植物种类的增加，传统的分类方法由 于提取的特征比较单一或者分类器结构过于简单，导致叶片识别率较低。为此，本文提出使用纹理特征结合形状 特征进行识别，并且使用深度信念网络构架作为分类器。纹理特征通过局部二值模式、Gabor 滤波和灰度共生矩阵 方法得到。而形状特征向量由 Hu 氏不变量和傅里叶描述子组成。为了避免过拟合现象，使用“dropout”方法训练 深度信念网络。这种基于多特征融合的深度信念网络的植物识别方法-Plant based
aco
- spd描述子，ACO算法匹配，文件中包含其他的描述子（形状上下文。。。），同时距离函数包括欧式距离和卡方距离(The SPD descr iptor matches the ACO algorithm, and the file contains other descr iptors (shape context) At the same time, the distance function includes Euclidean distance and chi square distance
fuliyemiaoshuzi
- 傅里叶描述子用于图像特征提取，对图像缩放，平移和旋转具有转换不变性，适合形状特征的提取(The Fourier descr iptor is used for image feature extraction, the image zooming, translation and rotation are invariant and suitable for the extraction of shape features.)