Fast Searching For The Optimal Area Of TFV Representation

Abstract

Visual images are often characterized by the distribution of certain key features. Taking the face image as an example, the eye, nose and mouth are often regarded as characterizing features for recognizing face image. We call these aspects structural and statistical information of visual images and aim for developing framework for the unified description of them. We extracts certain features from randomly chosen subareas, these features have good capability to represent the local texture information. We show our retrieval results over the public face database. We found that certain subareas can provide quite good retrieval results, but the thorough searching for such subareas are time-consuming. We further developed a simple fast searching method which can large simplifies the searching process, while in the same time preserve the good performance.