The employment of person identification patterns in e. facilities The aim of this work is to examine the importance of person identification in e. facilities, i.e. to find out how the persons can be identified and advantages for both identified person and the supplier of facilities. To reach the goal these tasks were raised: - to describe the conceptions and peculiarities of information society and person identification; - to describe the e. government, e. facilities and their peculiarities; - to analyse the person identification models and the level of identification in e. facilities; - to investigate the level of person identification in the most popular e. facilities in Lithuania. Object of the work: the models of person identification. Methods of investigation used in the work: - analysis of scientific literature,- the concepts and theories of information society, e. government and e. facilities were examined. The review of the results achieved by scientific investigation of other authors has been done. The analysis was carried out with reference to information found in books, monographs, conference theses and the net; - the review of documents and laws,- various documents and laws proposed by European Commission, European Parliament and the Republic of Lithuania have been examined. Public e. facilities nowadays are one of the most important parts of government strategies in many countries. Very often government envisages the benefit moving from ordinary public... [to full text]

Identifying people in historical photographs is an important task in many fields, including history, journalism, genealogy, and collecting. A wide variety of different methods, such as manual analysis, facial recognition, and crowdsourcing, have been used to identify the unknown photos. However, because of the large numbers of candidates and the poor quality or lack of source evidence, accurate historical person identification still remains challenging. Researchers especially struggle with the ``last mile problem" of historical person identification, where they must make a selection among a small number of highly similar candidates. Collaboration, including both human-AI collaboration and collaboration within human teams, has shown the advantages of improving data accuracy, but there is lack of research about how we can design a collaborative workspace to support the historical person identification. In this work, we present SleuthTalk, a web-based collaboration tool integrated into the public website Civil War Photo Sleuth which addresses the last-mile problem in historical person identification by providing support for shortlisting potential candidates from face recognition results, private collaborative workspaces, and structured feedback interfaces. We evaluated this feature in a mixed-method study involving 6 participants, who spent one week each using SleuthTalk and a comparable social media platform to identify an unknown photo. The results of this study show how our design helps with identifying historical photos in a collaborative way and suggests directions for improvement in future work. / Master of Science / Identifying people in historical photographs is an important task in many fields, including history, journalism, genealogy, and collecting. A wide variety of different methods, such as manual analysis, facial recognition, and crowdsourcing, have been used to identify the unknown photos. However, because of the large numbers of candidates and the poor quality or lack of source evidence, accurate historical person identification still remains challenging. Researchers especially struggle with the ``last mile problem" of historical person identification, where they must make a selection among a small number of highly similar candidates. Collaboration, including both human-AI collaboration and collaboration within human teams, has shown the advantages of improving data accuracy, but there is lack of research about how we can design a collaborative workspace to support the historical person identification. In this work, we present SleuthTalk, a web-based collaboration tool integrated into the public website Civil War Photo Sleuth which addresses the last-mile problem in historical person identification by providing support for shortlisting potential candidates from face recognition results, private collaborative workspaces, and structured feedback interfaces. We evaluated this feature in a mixed-method study involving 6 participants, who spent one week each using SleuthTalk and a comparable social media platform to identify an unknown photo. The results of this study show how our design helps with identifying historical photos in a collaborative way and suggests directions for improvement in future work.

Deformable modeling of facial soft tissues have found use in application domains such as human-machine interaction for facial expression recognition. More recently, such modeling techniques have been used for tasks like age estimation and person identification. This dissertation is focused on development of novel image analysis algorithms to follow facial strain patterns observed through video recording of faces in expressions. Specifically, we use the strain pattern extracted from non-rigid facial motion as a simplified and adequate way to characterize the underlying material properties of facial soft tissues. Such an approach has several unique features. Strain pattern instead of the image intensity is used as a classification feature. Strain is related to biomechanical properties of facial tissues that are distinct for each individual. Strain pattern is less sensitive to illumination differences (between enrolled and query sequences) and face camouflage because the strain pattern of a face remains stable as long as reliable facial deformations are captured. A finite element modeling based method enforces regularization which mitigates issues (such as temporal matching and noise sensitivity) related to automatic motion estimation. Therefore, the computational strategy is accurate and robust. Images or videos of facial deformations are acquired with video camera and without special imaging equipment. Experiments using range images on a dataset consisting of 50 subjects provide the necessary proof of concept that strain maps indeed have a discriminative value. On a video dataset containing 60 subjects undergoing a particular facial expression, experimental results using the computational strategy presented in this work emphasize the discriminatory and stability properties of strain maps across adverse data conditions (shadow lighting and face camouflage). Such properties make it a promising feature for image analysis tasks that can benefit from such auxiliary information about the human face. Strain maps add a new dimension in our abilities to characterize a human face. It also fosters newer ways to capture facial dynamics from video which, if exploited efficiently, can lead to an improved performance in tasks involving the human face. In a subsequent effort, we model the material constants (Young's modulus) of the skin in sub-regions of the face from the motion observed in multiple facial expressions. On a public database consisting of 40 subjects undergoing some set of facial motions, we present an expression invariant strategy to matching faces using the Young's modulus of the skin. Such an efficient way of describing underlying material properties from the displacements observed in video has an important application in deformable modeling of physical objects which are usually gauged by their simplicity and adequacy. The contributions through this work will have an impact on the broader vision community because of its highly novel approaches to the long-standing problem of motion analysis of elastic objects. In addition, the value is the cross disciplinary nature and its focus on applying image analysis algorithms to the rather difficult and important problem of material property characterization of facial soft tissues and their applications. We believe this research provides a special opportunity for the utilization of video processing to enhance our abilities to make unique discoveries through the facial dynamics inherent in video.

Informacinių technologijų pasiekimų pritaikymas valstybės valdymui atveria naujas didžiules galimybes gyventojų bendradarbiavimui su valdžios institucijomis, skaidresniam valdymui, aiškesniam sprendimų priėmimui. Jis sudaro gyventojui visiškai naujas galimybes bendrauti ir dirbti su viešojo administravimo institucijomis sau patogiu laiku, bet kurioje vietoje ir įvairiais būdais. Kai paslaugos pradėtos perkelti į elektroninę erdvę, iškilo svarbus klausimas: kaip atpažinti asmenį prieš suteikiant jam informaciją? Prieš pateikiant duomenis informacijos tiekėjas turi įsitikinti, kad perduoda duomenis būtent tam asmeniui, kuris padarė užklausą. Atitinkamai užklausą padaręs asmuo turi autentifikuoti save, arba kitaip sakant įrodyti savo tapatybę. E-valdžios koncepcijoje taip pat buvo planuota sukurti asmens identifikavimo sistemą, atitinkančią Europos Sąjungos reikalavimus. Ji turėtų neklystamai identifikuoti asmenį ir informacinių technologijų pagalba bendrauti su viešojo administravimo institucijomis. Darbo tikslas – įvertinti galimus ir perspektyvius asmens identifikavimo būdus; išanalizuoti jų patikimumo, saugumo ir sąveikumo aspektus; pateikti numatomų priemonių rekomendacijas. Uždaviniai: 1. išnagrinėti esamus bei alternatyvius asmens identifikavimo elektroninėje erdvėje būdus; 2. apžvelgti naujausių technologijų siūlomus asmens identifikavimo būdus; 3. išanalizuoti geriausius asmens identifikavimo pavyzdžius Europos Sąjungoje bei kitose užsienio šalyse; 4. atlikus tyrimą... [toliau žr. visą tekstą] / Adaptation of information technologies to the country’s administration opens up new opportunities for residents’ cooperation with the governmental institutions, for more transparent administration and clearer decision-making process. It also presents new possibilities for a citizen to communicate and work with public administration institutions on convenient time, place and ways. When some services were moved to electronic space, an important question was raised: how to recognise people before any information was presented to them? Information supplier has to make sure he was transferring requested information to the person who had placed the request. Also, the person, who placed the request, has to identify himself or to prove his identity. The identification system meeting the requirements of the European Union was also planned to be created while drafting the concept of e-government. This system should infallibly identify a person and communicate with public administration institution with the help of information technologies. The aim of the paper – is to evaluate possible and promising person identification ways; to analyse the aspects of their reliability, safety and interaction; and to supply recommendations of anticipatory measures. Objectives: 1. to discuss current and alternative ways to identify a person in electronic space; 2. to review identification solutions presented by the newest information technologies; 3. to analyse the best examples of person... [to full text]

In this thesis, person identification by combining automatic face and iris recognition is analyzed. Person identification by his face is one of the most intuitive from all biometric measures. We are used to recognizing familiar faces and confirming identity by a short glance at one's id card which contains image of the face. We are also used to being observed by surveillance cameras, which can perform biometric authentication without even being noticed. However, facial biometrics is one of most unstable metrics because the face gets noticeably older in several years and can frequently change depending on the mood of its owner. The core algorithm for facial recognition presented in this work is based on Gabor features. Deep analysis of each step helped to develop the method with better or similar accuracy to the best published results received on the same datasets, while being simple and fast. On the other hand, person identification by his iris is one of the most sophisticated, stable and accurate biometrics. The core algorithm for iris recognition presented in this work is based on a novel iris texture representation by local extremum points of multiscale Taylor expansion. The proposed irises comparison method is very different from the classic phase-based methods, but is also fast and accurate. Combining it with our implementation of phase-based method results in superior recognition accuracy which is comparable or better than any published results received on the same... [to full text] / Darbe tyrinėjama asmens identifikacija, kombinuojant automatinį veido ir akies rainelės atpažinimą. Automatinė identifikacija pagal veidą yra intuityviausia iš biometrijos metrikų, kadangi būtent pagal veidą mes geriausiai sugebame atpažinti pažįstamus asmenis. Tai yra ir viena labiausiai priimtinų, kadangi visi esame įprate, kad mus filmuoja apsaugos kameros, lengviausiai išmatuojama - nes nereikalauja jokių įmantrių skanerių, tačiau kartu - tai yra ir viena iš nestabiliausių metrikų, kadangi veidas sensta ir šiaip kinta priklausomai nuo savininko nuotaikos. Darbe pristatomas veidų atpažinimo algoritmas paremtas Gaboro požymiais. Nuodugni analizė padėjo sukurti algoritmą, kurio tikslumą vertinant standartiniais testais jis lenkia arba yra lygus su geriausiais publikuotais metodais, tačiau pasižymi paprastumu ir dideliu greičiu. Tuo tarpu automatinė identifikacija pagal rainelę yra laikoma viena stabiliausių ir tiksliausių. Darbe pristatomas rainelių atpažinimo algoritmas naudoja naujovišką rainelių tekstūros vaizdavimo būdą, paremtą lokaliais dvimačiais funkcijų aproksimacijos Teiloro eilutėmis ekstremumais. Kartu pristatomas naudojamų požymių palyginimo metodas, kuris yra labai nutolęs nuo bet kokių iki šiol rainelių tekstūrų palyginimui naudojamų metodų. Pasiūlytas rainelių atpažinimo metodas vėlgi yra spartus ir itin tikslus, o sujungus su klasikinio stiliaus rainelių tekstūrų palyginimu tikslumu nenusileidžia geriausiems publikuotiems metodams. Darbas užbaigiamas veidų... [toliau žr. visą tekstą]

Darbe tyrinėjama asmens identifikacija, kombinuojant automatinį veido ir akies rainelės atpažinimą. Automatinė identifikacija pagal veidą yra intuityviausia iš biometrijos metrikų, kadangi būtent pagal veidą mes geriausiai sugebame atpažinti pažįstamus asmenis. Tai yra ir viena labiausiai priimtinų, kadangi visi esame įprate, kad mus filmuoja apsaugos kameros, lengviausiai išmatuojama - nes nereikalauja jokių įmantrių skanerių, tačiau kartu - tai yra ir viena iš nestabiliausių metrikų, kadangi veidas sensta ir šiaip kinta priklausomai nuo savininko nuotaikos. Darbe pristatomas veidų atpažinimo algoritmas paremtas Gaboro požymiais. Nuodugni analizė padėjo sukurti algoritmą, kurio tikslumą vertinant standartiniais testais jis lenkia arba yra lygus su geriausiais publikuotais metodais, tačiau pasižymi paprastumu ir dideliu greičiu. Tuo tarpu automatinė identifikacija pagal rainelę yra laikoma viena stabiliausių ir tiksliausių. Darbe pristatomas rainelių atpažinimo algoritmas naudoja naujovišką rainelių tekstūros vaizdavimo būdą, paremtą lokaliais dvimačiais funkcijų aproksimacijos Teiloro eilutėmis ekstremumais. Kartu pristatomas naudojamų požymių palyginimo metodas, kuris yra labai nutolęs nuo bet kokių iki šiol rainelių tekstūrų palyginimui naudojamų metodų. Pasiūlytas rainelių atpažinimo metodas vėlgi yra spartus ir itin tikslus, o sujungus su klasikinio stiliaus rainelių tekstūrų palyginimu tikslumu nenusileidžia geriausiems publikuotiems metodams. Darbas užbaigiamas veidų... [toliau žr. visą tekstą] / In this thesis, person identification by combining automatic face and iris recognition is analyzed. Person identification by his face is one of the most intuitive from all biometric measures. We are used to recognizing familiar faces and confirming identity by a short glance at one's id card which contains image of the face. We are also used to being observed by surveillance cameras, which can perform biometric authentication without even being noticed. However, facial biometrics is one of most unstable metrics because the face gets noticeably older in several years and can frequently change depending on the mood of its owner. The core algorithm for facial recognition presented in this work is based on Gabor features. Deep analysis of each step helped to develop the method with better or similar accuracy to the best published results received on the same datasets, while being simple and fast. On the other hand, person identification by his iris is one of the most sophisticated, stable and accurate biometrics. The core algorithm for iris recognition presented in this work is based on a novel iris texture representation by local extremum points of multiscale Taylor expansion. The proposed irises comparison method is very different from the classic phase-based methods, but is also fast and accurate. Combining it with our implementation of phase-based method results in superior recognition accuracy which is comparable or better than any published results received on the same... [to full text]

The Self-Administered Interview© (SAI©) is an eyewitness interviewing tool designed to help protect eyewitness memory and elicit a comprehensive initial statement (Gabbert, Hope, & Fisher, 2009). Early research shows promising results in general adult samples. Whether the SAI© is an effective tool for older adult witnesses has not yet been fully addressed. Older adults will become increasingly important as a witness population in the future, yet perform worse compared to young adults. Some attempts have been made to aid older adult witnesses, but an easy-to-apply and effective method is yet to be introduced. This dissertation presents an overview of current knowledge on eyewitnesses and provides a theoretical basis for the empirical chapters. It further presents results of a systematic review and several meta-analyses on the effectiveness of the SAI© as a means to enhance eyewitness testimony. The meta-analyses cover 38 experimental comparisons from 22 empirical studies representing 1712 interviewees. Results indicate a strong benefit of the SAI both immediately after the witnessed crime (d = 1.20) and in a delayed recall (d = 0.92 compared to no initial recall) after one to three weeks. The third large chapter of this dissertation presents the results of an experiment that investigated the effectiveness of the SAI© for older witnesses’ testimony, suggestibility and lineup performance. 144 participants, half of which were 60 years or older and half aged 18-30 years, took part in two sessions. In the first session, they were shown a film of a staged crime and either filled in the SAI©, gave a written free recall or no initial recall. In the second session after one week they were then asked to give a free recall of what they remembered, answer questions including suggestive questions, and also to identify the perpetrator from the film from a 6-person simultaneous photo lineup. Results confirm the classic SAI© effect for young adults, show a small beneficial effect for older adults and also indicate a beneficial effect for lineup performance for the first time.

Cette thèse traite de l’identification des locuteurs et des visages dans les journaux télévisés. L’identification est effectuée à partir des noms affichés à l’écran dans les cartouches qui servent couramment à annoncer les locuteurs. Puisque ces cartouches apparaissent parcimonieusement dans la vidéo, obtenir de bonnes performances d’identification demande une bonne qualité du regroupement audiovisuel des personnes. Par regroupement, on entend ici la tâche de détecteret regrouper tous les instants où une personne parle ou apparaît. Cependant les variabilités intra-personnes gênent ce regroupement. Dans la modalité audio, ces variabilités sont causées par la parole superposée et les bruits de fond. Dans la modalité vidéo, elles correspondent essentiellement à des variations de la pose des visages dans les scènes de plateaux avec, en plus, des variations de luminosité (notamment dans le cas des reportages). Dans cette thèse, nous proposons une modélisation du contexte de la vidéo est proposée afin d’optimiser le regroupement pour une meilleure identification. Dans un premier temps, un modèle basé sur les CRF est proposé afin d’effectuer le regroupement audiovisuel des personnes de manière jointe. Dans un second temps, un système d’identification est mis en place, basé sur la combinaison d’un CRF de nommage à l’échelle des classes, et du CRF développé précédemment pour le regroupement. En particulier, des informations de contexte extraites de l’arrière plan des images et des noms extraits des cartouches sont intégrées dans le CRF de regroupement. Ces éléments permettent d’améliorer le regroupement et d’obtenir des gains significatifs en identification dans les scènes de plateaux. / This Phd thesis is about speaker and face identification in broadcast news. The identification is relying on the names automatically extracted from overlaid texts which are used to announce the speakers. Since those names appear sparsely in the video, identification performance depends on the diarization performance i.e. the capacity of detecting and clustering together all the moments when a given person appears or speaks. However, intra-person variability in the video signal make this task difficult. In the audio modality, this variability comes from overlap speech and background noise. For the video, it consists in head pose variations and lighting conditions (especially in report scenes). A context-aware model is proposed to optimize the diarization for a better identification. Firstly, a Conditional Random Field (CRF) model isproposed to perform the diarization jointly over the speech segments and the face tracks. Secondly, an identifcation system is designed. It is based on the combination of a naming CRF at cluster level and the diarization CRF. In particular, context information extracted from the image background and the names extracted from the overlaid texts are integrated in the diarization CRF at segment level. The use of those elements enable us to obtain better performances in diarization and identification, especially in studio scenes.

This thesis deals with problems of identification cards at the University of Economics, Prague. Its primary goal is to consider and evaluate the possibility of a transfer of the ID card management into the ISIS system. The thesis consists of four parts. The first one offers a complex analysis of the ID card management at the University. The second one analyses two ID card management systems: the NESA system, which is being used at the University now, and the ISIS system, which could also be used for the ID card management. The third part includes a proposal of adjustments in the ISIS system, which would make its ID card management implementation comply with the University's needs. The proposal describes general features of the system, relations to its environs and a graphical user interface. Finally the last part covers the actual state of the project and its differences from the proposal offered in the thesis. Information sources for the thesis were legal norms, University regulations and internal documents as well as the author's knowledge and experience gained through several years of the NESA system maintenance and numerous consultations with the University ID card management staff and ISIS developers. The main assets of this thesis lay in the comprehensive view of the ID card management at the University along with the proposal of the new ID card management system, which is to be integrated into ISIS.

This paper is dealing with the detection clothes characteristics in the picture, for the use of person identification. These characteristics are described and categorized. It also deals with the design of the database structure, which works with masks and categories of characteristics for their processing. This work uses haar cascades to detect face and to determine the position of clothing for the purpose of color detection