人脸识别现有应用介绍 人脸识别 汉王 飞瑞斯 中控
采用LBP金字塔的人脸描述与识别脸识别 多尺度分析 LBP金字塔 直方图
UCI多特征数据库的原始文献，handwriten digit recognition by combined classifiers
A feature-based approach to visual/IR sensor image registra- tion is presented.This new method overcomes the difficulties caused by the discrepancy in data’s gray-scale characteristics and the problem of feature inconsistency.It employs a wavelet-based feature extractor to locate point features from contours based on local statistics of the image intensity.Matching is carried out at multiresolution levels based on point features.A consistency-checking step is involved to eliminate mis- matches.The algorithm is accurate,robust,and fast.It is capable of handling images with considerable translation,scaling,and rotation.De- tails on the registration algorithm including feature extraction,matching, consistency checking,and the image transformation model are dis- cussed.Experimental results using real visual/IR sensor data are presented.
The primary goal of pattern recognition is supervised or unsupervised classification.Among the various frameworks in which pattern recognition has been traditionally formulated,the statistical approach has been most intensively studied and used in practice.More recently,neural network techniques and methods imported from statistical learning theory have been receiving increasing attention.The design of a recognition system requires careful attention to the following issues:definition of pattern classes, sensing environment,pattern representation,feature extraction and selection,cluster analysis,classifier design and learning,selection of training and test samples,and performance evaluation.In spite of almost 50 years of research and development in this field,the general problem of recognizing complex patterns with arbitrary orientation,location,and scale remains unsolved.New and emerging applications,such as data mining,web searching,retrieval of multimedia data,face recognition,and cursive handwriting recognition, require robust and efficient pattern recognition techniques.The objective of this review paper is to summarize and compare some of the well-known methods used in various stages of a pattern recognition system and identify research topics and applications which are at the forefront of this exciting and challenging field.