| 摘要 |
A method and apparatus is described that categorizes images by extracting regions and describing the regions with a set of 15-dimensional image patch feature vectors, which are concatenations of color and texture feature vectors. By comparing the image patch feature vectors in images with similarly-obtained image patch vectors in a Gaussian mixture based model pool (obtained in an image patch modeling phase), the images may be categorized (in an image patch recognition phase) with probabilities relating to each image patch. Higher probabilities are likelier correlations. The device may be a single or multiple core CPU, or parallelized vector processor for characterizing many images. The images may be photographs, videos, or video stills, without restriction. When used real-time, the method may be used for visual searching or sorting. |
