CENSUS HISTOGRAMS: A SIMPLE FEATURE EXTRACTION and MATCHING APPROACH FOR FACE RECOGNITION

Most face recognition approaches require a prior training where a given distribution of faces is assumed to further predict the identity of test faces. Such an approach may experience difficulty in identifying faces belonging to distributions different from the one provided during the training. A face recognition technique that performs well regardless of training is, therefore, interesting to consider as a basis of more sophisticated methods. In this work, the Census Transform is applied to describe the faces. Based on a scanning window which extracts local histograms of Census Features, we present a method that directly matches face samples. With this simple technique, 97.2% of the faces in the FERET fa/fb test were correctly recognized. Despite being an easy test set, we have found no other approaches in literature regarding straight comparisons of faces with such a performance. Also, a window for further improvement is presented. Among other techniques, we demonstrate how the use of SVMs over the Census Histogram representation can increase the recognition performance.

Improving face recognition with multispectral fusion and support vector machines

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Infrared face recogniton by optimum-path forest

This paper presents a novel, fast and accurate appearance-based method for infrared face recognition. By introducing the Optimum-Path Forest classifier, our objective is to get good recognition rates and effectively reduce the computational effort. The feature extraction procedure is carried out by PCA, and the results are compared to two other well known supervised learning classifiers; Artificial Neural Networks and Support Vector Machines. The achieved performance asserts the promise of the proposed framework. ©2009 IEEE.

Frontal sinus recognition for human identification

Many methods based on biometrics such as fingerprint, face, iris, and retina have been proposed for person identification. However, for deceased individuals, such biometric measurements are not available. In such cases, parts of the human skeleton can be used for identification, such as dental records, thorax, vertebrae, shoulder, and frontal sinus. It has been established in prior investigations that the radiographic pattern of frontal sinus is highly variable and unique for every individual. This has stimulated the proposition of measurements of the frontal sinus pattern, obtained from x-ray films, for skeletal identification. This paper presents a frontal sinus recognition method for human identification based on Image Foresting Transform and shape context. Experimental results (ERR = 5,82%) have shown the effectiveness of the proposed method.

Adaptative techniques for the human faces detection

This paper presents results from an efficient approach to an automatic detection and extraction of human faces from images with any color, texture or objects in background, that consist in find isosceles triangles formed by the eyes and mouth.

Digital monitoring of broiler breeder behavior for assessment of thermal welfare

The assessment of welfare issues has been a challenge for poultry producers, and lately welfare standards needs to be reached in order to agree with international market demand. This research proposes the use of continuous behavior monitoring in order to contribute for assessing welfare. A software was developed using the language Clarium. The software managed the recording of data as well as the data searching in the database Firebird. Both software and the observational methodology were tested in a trial conducted inside an environmental chamber, using three genetics of broiler breeders. Behavioral pattern was recorded and correlated to ambient thermal and aerial variation. Monitoring video cameras were placed on the roof facing the used for registering the bird's behavior. From video camera images were recorded during the total period when the ambient was bright, and for analyzing the video images a sample of 15min observation in the morning and 15 min in the afternoon was used, adding up to 30 min daily observation. A specific model so-called behavior was developed inside the software for counting specific behavior and its frequency of occurrence, as well as its duration. Electronic identification was recorded for 24h period. Behavioral video recording images was related to the data recorded using electronic identification.. Statistical analysis of data allowed to identify behavioral differences related to the change in thermal environment, and ultimately indicating thermal stress and departure from welfare conditions.

A video-based biometric authentication for e-learning web applications

In the last years there was an exponential growth in the offering of Web-enabled distance courses and in the number of enrolments in corporate and higher education using this modality. However, the lack of efficient mechanisms that assures user authentication in this sort of environment, in the system login as well as throughout his session, has been pointed out as a serious deficiency. Some studies have been led about possible biometric applications for web authentication. However, password based authentication still prevails. With the popularization of biometric enabled devices and resultant fall of prices for the collection of biometric traits, biometrics is reconsidered as a secure remote authentication form for web applications. In this work, the face recognition accuracy, captured on-line by a webcam in Internet environment, is investigated, simulating the natural interaction of a person in the context of a distance course environment. Partial results show that this technique can be successfully applied to confirm the presence of users throughout the course attendance in an educational distance course. An efficient client/server architecture is also proposed. © 2009 Springer Berlin Heidelberg.

A graph-based framework for thermal faceprint characterization

Thermal faceprint has been paramount in the last years. Since we can handle with face recognition using images acquired in the infrared spectrum, an unique individual's signature can be obtained through the blood vessels network of the face. In this work, we propose a novel framework for thermal faceprint extraction using a collection of graph-based techniques, which were never used to this task up to date. A robust method of thermal face segmentation is also presented. The experiments, which were conducted over the UND Collection C dataset, have showed promising results. © 2011 Springer-Verlag.

Biomobile: sistema de identificação de usuários em dispositivos móveis na plataforma Android utilizando reconhecimento de faces a partir de vídeo

Pós-graduação em Ciência da Computação - IBILCE

Análise de técnicas de reconhecimento de padrões para a identificação biométrica de usuários em aplicações WEB Utilizando faces a partir de vídeos

Pós-graduação em Ciência da Computação - IBILCE

Autenticação biométrica de usuários em sistemas de E-learning baseada em reconhecimento de faces a partir de vídeo

Pós-graduação em Ciência da Computação - IBILCE

Reconhecimento de faces 3D com Kinect

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Aplicação de sistemas imunológicos artificiais para biometria facial: Reconhecimento de identidade baseado nas características de padrões binários

Pós-graduação em Engenharia Elétrica - FEIS