Study On Some Key Issuses In Face Recognition And Application Under Unlimited Conditions

The study on Automatic Face Recognition(AFR) has both significant theoretic values and bright future of applications. Since this century's beginning, AFR technology has made great progress and obtains satisfactory results under limited conditions, some AFR commercial systems have successfully applied in some fields. However, practice has proved that AFR still has many existing technical problems to be solved under unlimited conditions. This paper does some research on several key technologies of AFR about the above problems.The main contributions of this thesis are as follows:1. Provided a thorough survey of face detection and recognition on history and research situationThis paper provides a detailed survey of research in the area of face detection on three aspects:knowledge-based approach,statistical-learning-based approach and skin-color-model-based approach, and reviews the latest findings of face detection generally. Then, the research of face recognition is reviewed from three historical stages, classical algorithms in every stage are analysised. Moreover, generally introduce the famous research institutes(groups) of AFR both abroad and in China and summarizes the important resources related to AFR, such as face databases, the top international conferences, authoritative journals and famous tests on AFR. Finally, introduce the key technical difficulties in the applications of AFR depending on those tests results.2. Studied face detection under unlimited conditions(1) Proposed a new method for skin color model under illumination variationsThe proposed method trains a robust skin color model using the YCbCr values of selected samples. The experimental results show that this model achieves a good performance on face skin region detection under illumination variations, with the support of 4-connected regions detection and the face skin region recovery technology, proposed skin color model can detect and locate the face regions accurately.(2) Proposed a face detection method based on SMQT+SNoW+SVMThe SMQT+SNoW method has some disadvantages such as low speed and high false positive rate when applied to face detection. In order to solve those problems, this paper presents a modified method to detect faces using the strategy of pre-detection of skin region and SVM classification. First, search the potential face regions using the proposed skin color model, then, calculate the regions' feature values by SMQT, finally, detect the real faces accurately using the classification of SNow+SVM. The experiment on 1000 face images under illumination variations shows that proposed method performances very well on speed and correct rate, at the same time, the false positive rate also has a marked reduction and can meet demand of practical applications.(3) Proposed a multi-view face detection method under illumination variations based on FloatBoostThis method firstly search the potential face regions using the proposed skin color model, then, chroma map is adopted to obtain the four-connected components from the skin color segmentation blocks, label them, and identify the center of each block, finally, the faces verification is performed through the classifier based on FloatBoost. Comparing with some other previous algorithms for multi-view face detection, our method not only effectively improves the right detection rate of multi-view faces under illumination variations, but also obviously decreases the time consumption and operation complexity, and at the same time, the located faces position are more accurate and be good for improving the accuracy of feature extrication in next face recognition step.3. Studied face recognition under unlimited conditions(1) Proposed a new method for face recognition under illumination variations based on ULBP and SVMFirst, the proposed method applies two-degree ULBP to extract Illumination invariant feature on multi-block face, second, combines those histogram features into the final identification characteristics in the right order, then, SVM is applying to feature classification to realize the face recognition under illumination variations. The experiment on YaleB database shows that, the combination of multi-degree and multi-block feature extraction method based on ULBP performances well both details and universe on extracting the illumination invariant face feature and achieves a high face recognition rate.(2) Proposed an efficient method to locate key face feature points and estimate the head pose accuratelyThis method first calculates a face map using chroma information, binary it and search the four-connected regions on binary result. Second, eliminates the regions which do not follow proposed rules, then the key face feature points are located accurately. Finally, the head pose is estimated by using the above feature points. (3) Proposed a Multi-view face recognition method based on horizontal mirror technology and decision-level image fusionThe proposed method first generates more face training samples by horizontal mirror technology, then, estimates the head pose of each of them and classifies it to one of seven corresponding pose spaces decomposing from the pose range of-90 to +90. Second, extracts the face feature by Gabor wavelet and reduces the feature dimension using 2DPCA to make seven feature sub-spaces. when recognition begin, firstly, makes input face's horizontal mirror image, secondly, extracts their face feature and estimate their head pose using the same method, and projects them to corresponding feature sub-space, finally, calculates the projection Euclidean distance and achieves the recognition result by decision-level image fusion. The experiments on ORL,ColorFeret and Cas-Peal database show that it can obtain satisfactory result on pose range of-90 to+90 with few training samples.4. Design and realize an online face recognition systemThis paper describes in detail how to design an online face recognition system from the construction of information database,the development of client/server background server programs and the design of website, gives the process flow diagram and experiment result. The proposed system has been applied to smart access and performance well.This thesis provides some new methods to solve the problems of face detection and recognition under unlimited conditions, the proposed methods have been applied to an online face recognition system.