local self-similaritySIFTPCAregion descriptionimage matchingThe advanced descriptor, i.e., Local Self-Similarities (LSS), is successfully adopted for object classification and scene recognition. However, it is only invariance against small geometric and photometric transformations. In this paper, two low...
The local self-similarity descriptor is a kind of important image or video local feature description method. It is often used for detection, identification and recognition. In this paper we propose a new local self-similarity descriptor based on structural similarity (SSIM) index. It is showed in...
Here are some options: 1. Take a histogram after converting your image to log polar coordinates. The following thread has some code for converting to log-polar coordinates:
To address the problems of the above-mentioned image representation based registration methods, we have proposed a new similarity metric based on the self-similarity inspired local descriptor. The notion of self-similarity has been explored by the nonlocal means for image denoising [51], segmentation...
Self-similarity remains relatively invariant to the photo/sketch-modality variation therefore reduces the modality gap before NN matching. A new face descriptor, Local Radon Binary Pattern (LRBP) was proposed by Galoogahi et al. [103] to directly match face photos and sketches. In the LRBP ...
Nalewajski RF, Parr RG (2000) Information theory, atoms in molecules, and molecular similarity. Proc Natl Acad Sci USA 97:8879–8882 ArticleCAS Kullback S, Leibler RA (1951) On information and sufficiency. Ann Math Stat 22:79–86
Three dimensional shape comparison of flexible proteins using the local-diameter descriptor p pBackground/p pTechniques for inferring the functions of the protein by comparing their shape similarity have been receiving a lot of attention. Proteins... Y Fang,YS Liu,K Ramani - 《Bmc Structural ...
The match kernel formulation in (4) interprets deep local descriptor similar- ity as similarity accumulation for all pairs of positions on the n × n grid. It reveals that matching between convolu- tional descriptors in φa and φb is performed in a translation variant way. The...
我们要回归cnn一开始的设计思想。cnn一开始是面向目标实体识别的任务的。它就是要模拟人的认知方式，达到...
In this paper, we present 3DMatch, a data-driven model that learns a local volumetric patch descriptor for establishing correspondences between partial 3D data. To amass training data for our model, we propose a self-supervised feature learning method that leverages the millions of correspondence ...