A sparse texture representation using local affine regions
A sparse texture representation using local affine regions
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DOI：
10.1109/tpami.2005.151
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发表时间：
2005-08-01
影响因子：
23.6
通讯作者：
Ponce, J
中科院分区：
文献类型：
--
作者：
Lazebnik, S;Schmid, C;Ponce, J
本文介绍了一种纹理表示法，适用于各种变换下的纹理表面图像的识别，包括视点变化和非刚性变形。在特征提取阶段，在图像中发现一组稀疏的仿射Harris和Laplace区域。这些区域中的每一个都可以被认为是具有特征椭圆形状和独特外观图案的纹理元素。该模式是通过形状归一化过程以仿射不变的方式捕获的，然后计算两个新的描述符，自旋图像和裂隙描述符。当不需要仿射不变性时，原始椭圆形状作为纹理识别的附加判别特征。在检索和分类任务中，使用整个Brodatz数据库和从不同视点获取的1000张纹理表面照片的公开集合对所提出的方法进行了评估。
This paper introduces a texture representation suitable for recognizing images of textured surfaces under a wide range of transformations, including viewpoint changes and nonrigid deformations. At the feature extraction stage, a sparse set of affine Harris and Laplacian regions is found in the image. Each of these regions can be thought of as a texture element having a characteristic elliptic shape and a distinctive appearance pattern. This pattern is captured in an affine-invariant fashion via a process of shape normalization followed by the computation of two novel descriptors, the spin image and the RIFT descriptor. When affine invariance is not required, the original elliptical shape serves as an additional discriminative feature for texture recognition. The proposed approach is evaluated in retrieval and classification tasks using the entire Brodatz database and a publicly available collection of 1,000 photographs of textured surfaces taken from different viewpoints.