El presente proyecto presenta la viabilidad de la ejecución del modelo de negocio de un software integrado de reconocimiento facial, que mide el aforo de establecimientos, mediante un motor de búsquedas, Appforo dirigidos a los segmentos B2B y B2C, en relación a la investigación realizada en Lima Metropolitana de las personas entre las edades de 18 a 25 años, y empresas de los sectores de restaurantes, farmacias, boticas y otros establecimientos públicos comerciales. A partir de la investigación realizada permitió validar el modelo de negocio e identificar aquellos aspectos que era necesario reestructurar, este proyecto se pondrá en marcha durante el 2021, por lo que se establecieron proyecciones comerciales, teniendo en cuenta el macroentorno, microentorno, entre otros aspectos. Asimismo, se desarrolló el plan de Operaciones, Financiero, de Marketing, de Recursos Humanos y de Responsabilidad Social Empresarial. Al respecto, dentro de cada plan se determinó las estrategias a usar, el presupuesto asignado, en qué tiempo se realizaría y con qué frecuencia. En ese sentido, se estimó como resultado, que el proyecto requiere iniciar con una inversión de 30 mil 780.18 soles, con lo que obtendremos beneficios netos de 295 218.85, 512 462.89 y 912 675.67 soles en el primer, segundo y tercer año. / This project presents the feasibility of executing the business model of an integrated facial recognition software, which measures the capacity of establishments, through a search engine, Appforo aimed at the B2B and B2C segments, in relation to the research carried out in Metropolitan Lima of people between the ages of 18 to 25 years, and companies in the sectors of restaurants, pharmacies, drugstores and other commercial public establishments. Based on the research carried out, it allowed to validate the business model and identify those aspects that needed to be restructured, this project will be launched during 2021, for which commercial projections were established, taking into account the macro environment, micro environment, among other aspects. Likewise, the Operations, Financial, Marketing, Human Resources and Corporate Social Responsibility plan was developed. In this regard, within each plan, the strategies to be used were determined, the budget assigned, in what time it would be carried out and how often. In this sense, it was estimated as a result that the project requires starting with an investment of 30, 780.18 soles, with which we will obtain net benefits of 295 218.85, 512 462.89 y 912 675.67 soles in the first, second and third year. / Trabajo de investigación

Artificiell intelligens (AI) har tagit världen med storm de senaste åren där nya implementationer och uppfinningar ständigt tas fram och implementeras. Ansiktsigenkänning är en teknik inom AI som kan användas för att identifiera bland annat kriminella eller terrorister genom övervakningskameror, identifiera underåriga drickare och motverka identifikationsstöld. Problemet med ansiktsigenkänningstekniker är att det finns en brist på kunskap om människors attityd till ansiktsigenkänning. Samtidigt som utvecklingen av AI går i en rasande fart och användandet av AI ständigt ökar i samhället, hänger inte de etiska reflektionerna på användningen av AI med i den snabba tekniska utvecklingen av AI. Etiska reflektioner handlar om egenskaper, syften och tilliten till AI. Det vill säga, används ansiktsigenkänning på ett sätt som är allmänt accepterat av de som utsätts för tekniken. Detta är ett intressant ämne eftersom samhällen och världen befinner sig i denna utveckling just nu.    Denna studie har som syfte att försöka fylla bristen på kunskap om människors attityd till ansiktsigenkänning genom att analysera människors inställning till det. Studien som genomförs består av Twitter-data som ligger till grund för en sentimentanalys. En sentimentanalys består av en kombination av en kvalitativ och kvantitativ analys. Studiens resultat visar att inställningen till ansiktsigenkänning beror på kontexten eller situationen den används i och till vilket syfte. Enligt den Twitter-data som hämtades för denna studie, verkar inställningen till ansiktsigenkänning skilja sig mellan olika länder. Resultatet av denna studie har även likheter med tidigare studier som undersökt inställning till ansiktsigenkänning.   Studien avser att göra ett metodbidrag genom att processen för datahämtning samt dataanalys dokumenteras. I resultatet görs en granskning av attitydklassificeringen där verktyget som används för att avgöra inställning jämförs med vad två verkliga personer anser att inställningen i ett visst tweet är. Det visade att det fanns en stor skillnad mellan hur människorna i testet och verktyget som används klassificerade sentiment. / Artificial intelligence (AI) has taken the world by storm in recent years where new implementations and inventions are constantly being developed and implemented. Facial recognition is a technology in AI that can be used to identify criminals or terrorists through surveillance cameras, identify underage drinkers and counteract identity theft. The problem with facial recognition techniques is that there is a lack of knowledge about how people react toward them. At the same time as the development of AI is accelerating and the use of AI is constantly increasing in society, the ethical reflections on the use of AI are not part of the rapid technological development of AI. Ethical reflections are about characteristics, purposes, and trust in AI. That means analyzing if facial recognition is used in a way that is widely accepted by those who are exposed to it. This is an interesting topic because societies and the world are currently in this development.   The aim of this study is to try and fill the gaps in the lack of knowledge about people's attitude toward facial recognition by analyzing people's attitudes toward it. The study that is carried out consists of Twitter data, which undergoes a sentiment analysis, which is a combination of a qualitative and quantitative analysis. The results of the study show that the attitude toward facial recognition depends on the context or situation it is used for and for what purpose. According to the Twitter data that was obtained for this study, the attitude toward facial recognition seems to differ between different countries. The results of this study also have similarities with previous studies that examined attitudes toward facial recognition.   The study intends to make a method contribution by documenting the process for data retrieval and data analysis. The result includes a review of the attitude classification where the tool used to determine attitude is compared to what two real people think the attitude in a particular tweet is. It turned out that there was a big difference between how the people in the test and the tool used for the analysis classified sentiments.

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AI är ett ämne vars framsteg i dagsläget diskuteras flitigt. En liten funktion av fenomenet AI utgörs av ansiktsigenkänning, något som även det på senaste tiden implementerats på fler områden i vårt samhälle. Då tekniken i sig är relativt ny är polismyndighetens användning av verktyget likaså. Denna studie ämnar att undersöka vilka risker och möjligheter användningen av ansiktsigenkänning i svenska brottsutredningar har. Studien bygger på semistrukturerade intervjuer med personer tillhörande de två särskilt intressanta yrkesgrupperna AI-forskare och poliser. Detta för att frambringa två olika perspektiv. I analysen av empirin knyts de framtagna konsekvenserna an med teorin sociomaterialitet. Studien presenterar ett antal risker och möjligheter som bekräftar redan identifierade konsekvenser i litteraturen. Risker och möjligheter som identifierades var relaterade till integritet, lagstiftning, bias i databaser, övertro och misstro, effektivisering, trygghetsskapande, noggrannhet och arbetsmiljö. Studien avslutas med förslag på framtida forskning. / AI is a technology which development is frequently discussed. A small part of the phenomena AI is constituted by facial recognition, a technology which is rapidly implemented in an increasing number of societal functions. Since facial recognition itself is relatively new, the utilization of it within the police authority is as well. This study intends to investigate which risks and possibilities the utilization of facial recognition has in Swedish criminal investigations. The study is based on semi-structured interviews with people divided into one of two different interesting groups: AI-scientists and employees at the Swedish police authority. This, with the intention to capture two different perspectives. In the analysis of the empirical data the identified consequences are linked to the theory sociomateriality. The study presents a number of risks and possibilities which confirm already identified consequences in literature. The risks and possibilities identified related to integrity, laws and regulations, bias in databases, over-reliance and disbelief, efficiency, security enhancing, accuracy and working environment. The study concludes with suggestions for future research.

A currently ongoing project at Stanley Security is to develop a facial recognition system as access control system to prevent theft of heavy vehicles for terrorist purposes. As of today, there are several providers of facial recognition techniques and the spectrum ranges from multi dollar licenses to easy access open source. This fact, the range of different algorithms and the difficulty to estimate their differences in performance is the fundamental inspiration to investigate in this thesis. Four facial recognition algorithms, Eigenfaces, Fisherfaces, Local Binary Patterns Histogram and Convolutional Neural Network, that are easily accessible and open source were therefore chosen and investigated. They were implemented and tested on the STANLEY database. The STANLEY database was built up for this test specifically. It contains of 11 persons with 10 pictures each, taken from the driver’s seat, including sunglasses, various head sizes and strong local face lighting and shadowing to simulate the environment in which the algorithms were tested. The Convolutional Neural Network algorithm had the highest precision, the least false positives and was also the fastest in the speed test. The Eigenfaces and Fisherfaces algorithms were not very robust and had trouble with images where high local face lighting and shadowing were present and are therefore considered not suited for access control for heavy vehicles. The Local Binary Patters Histogram algorithm stood out from the Eigenfaces and Fisherfaces algorithms but was still not near the Convolutional Neural Network algorithm in performance. The Convolutional Neural Network algorithm had a precision or true positive rate of 95,8% of the persons on all the given images and had 0% false positives. The precision for the Eigenface, Fisherface and LBPH algorithms were 16.2%, 17,6% and 26,5% respectively and the true positives were 23,5%, 24,5% and 10,2% respectively. The high false positive rate would have negative impact on access control applications. The convolutional neural network-based algorithm was concluded to be the facial recognition technique of choice for STANLEY Security and the biggest obstacle for implementing and commercializing this solution is the jurisdictional aspects regarding license and usage of code and specifically the pre-trained face recognition model. The jurisdictional aspect was never treated in this thesis although it was one of the extensions.

Denna studie undersöker anställdas inställning till BA som MFA-metod på svenska SMF, även vilken BA-metod som anses lämpligast för användning. Tidigare studier har främst fokuserat på större organisationer och företag med kvantitativa forskningsmetoder. Därav har denna studie valt att undersöka SMF med en kvalitativ inriktning i formen av en semistrukturerad intervjustudie. Studien genomförde totalt nio intervjuer från varierande företag med respondenter aven mängd olika arbetsroller. Utifrån dessa intervjuer kunde flera teman identifieras, dessa användes för att dra slutsatser kring användarens inställning och vilken BA-metod som föredras i företagskontext. Teman som identifierades utgjorde grunden förde anställdas inställning, exempelvis vilka positiva och negativa aspekter de anställda kunde se med BA som MFA. Resultaten visade att de anställda generellt sett var positivt inställda till BA som MFA-metod och att de flesta kunde tänka sig implementera detta på sin arbetsplats. Av fingeravtryck, röstigenkänning,ansiktsigenkänning och irisskanning föredrog respondenterna fingeravtryck som BA-metod i företagskontext. Studien valde att inte fokusera på företag som redan implementerat BA som MFA. Applikationer och program som anställda använder där BA erbjuds anses inte som att företaget implementerat BA som MFA. / This study examines employees' attitudes towards BA (Biometric Authentication) as an MFA (Multi-Factor Authentication) method at Swedish SMEs, as well as which BA method is considered most suitable for use. Previous studies have focused on larger organizations and companies with quantitative research methods. Therefore, this study has chosen to examine SMEs with a qualitative focus by conducting semistructured interviews. The study conducted a total of nine interviews from various companies with respondents from a variety of work roles. Based on these interviews, several themes could be identified, these were used to draw conclusions about the employees’ attitude and which BA method is preferred in a business context. Themes that were identified formed the basis for the employees' attitude, for example what positive and negative aspects the employees could see with BA as MFA. The results showed that the employees were generally positive about BA as an MFA method and that most could imagine implementing this in their workplace. Focusing on fingerprints, voice recognition, face recognition and iris scanning, the respondents preferred fingerprints as a BA method. The study chose not to focus on companies that have already implemented BA as MFA. Applications and programs that employees use where BA is offered are not considered that the company has implemented BA as MFA.

This thesis investigates the social, legal and ethical perceptions of participants towards the implementation of biometric access control systems within a sample of United Kingdom work-based environments. It focuses on the application of fingerprint scanning and facial recognition systems, whilst alluding to the development of more advanced (bleeding edge) technologies in the future. The conceptual framework is based on a tripartite model in which Maslow's Hierarchy of Needs is applied to the workforce whilst the principles of Utilitarianism and the Psychological Contract are applied to both management strategies and workforce perceptions. A qualitative paradigm is used in which semi-structured interviews are conducted with management and workforce participants within a sample of United Kingdom-based organisations (represented by Case Studies A-D). Discourse from these interviews are analysed, leading to the development of a series of first-cut findings for suggested "Best Practice " in the social, legal and ethical management of biometric access control systems. This process is subsequently developed with a refined sample of respondents (Case Studies A and C) culminating in the presentation of a suggested "Best Practice Model" for application to all four case studies. The model is based upon elements of a pre-determined Code of Practice (ISO/IEC 27002lnformation Technology - Security techniques - Code of Practice for Information Security Management) towards fostering acceptance of biometric technology within the workplace, in answering the question: How should organisations using biometric access control systems address social, legal and ethical concerns in the management of specific working environments in the United Kingdom?

La zeitgesit contemporaine sur la reconnaissance des visages suggère que le processus de reconnaissance reposerait essentiellement sur le traitement des distances entre les attributs internes du visage. Il est toutefois surprenant de noter que cette hypothèse n’a jamais été évaluée directement dans la littérature. Pour ce faire, 515 photographies de visages ont été annotées afin d’évaluer l’information véhiculée par de telles distances. Les résultats obtenus suggèrent que les études précédentes ayant utilisé des modifications de ces distances ont présenté 4 fois plus d’informations que les distances inter-attributs du monde réel. De plus, il semblerait que les observateurs humains utilisent difficilement les distances inter-attributs issues de visages réels pour reconnaître leurs semblables à plusieurs distances de visionnement (pourcentage correct maximal de 65%). Qui plus est, la performance des observateurs est presque parfaitement restaurée lorsque l’information des distances inter-attributs n’est pas utilisable mais que les observateurs peuvent utiliser les autres sources d’information de visages réels. Nous concluons que des indices faciaux autre que les distances inter-attributs tel que la forme des attributs et les propriétés de la peau véhiculent l’information utilisée par le système visuel pour opérer la reconnaissance des visages. / According to an influential view, based on studies of development and of the face inversion effect, human face recognition relies mainly on the treatment of the distances among internal facial features. However, there is surprisingly little evidence supporting this claim. Here, we first use a sample of 515 face photographs to estimate the face recognition information available in interattribute distances. We demonstrate that previous studies of interattribute distances generated faces that exaggerated 4 times this information compared to real-world faces. When interattribute distances are sampled from a real-world distribution, we show that human observers recognize faces poorly across a broad range of viewing distances (with a maximum accuracy of 65%). In contrast, recognition performance is restored when observers only use facial cues of real-world faces other than interattribute distances. We conclude that facial cues other than interattribute distances such as attribute shapes and skin properties are the dominant information of face recognition mechanisms.

Réalisé sous la co-direction de Linda Booij, Catherine Herba et Patricia Garel / Contexte : la présence d’un biais cognitif négatif chez les individus qui souffrent de dépression majeure (DM) et ceux qui y sont à haut risque (e.g. enfants de mères qui souffrent de DM) est maintenant établie. Aucune étude portant sur la vulnérabilité cognitive (VC) des membres de la fratrie n’est rapportée. Objectifs : la présente étude a pour but de vérifier si la fratrie des adolescents qui souffrent de DM présentent une VC qui les prédisposent à la DM. Méthode : cette étude porte sur 49 adolescents (18 participants traités pour une DM, 16 membres de la fratrie et 15 participants témoin), âgés entre 12 et 20 ans. La VC de chaque participant est quantifiée via un questionnaire qui mesure la réactivité cognitive (RC), soit le LEIDS-R, et une tâche de reconnaissance des expressions faciale (REF). La cognition sociale des participants est mesurée par le MASC, un outil qui évalue la cognition sociale par médium vidéo et que notre équipe a traduit de l’allemand au français. Résultats : les résultats préliminaires de la présente étude indiquent qu’une différence de réactivité cognitive est présente entre les adolescents traités pour une DM et les participants du groupe témoin (p < 0,001). L’analyse préliminaire tend à indiquer qu’une différence est présente entre la fratrie et le groupe contrôle. Conclusion : plusieurs de nos résultats tendent en faveur de la présence d’une VC prédisposant à la DM chez la fratrie des adolescents souffrant de DM. Ces résultats préliminaires doivent être confirmés par des études longitudinales. / Background: a negative cognitive bias is present among individuals who suffers from major depression. This bias is also reported among individuals at high risk of major depression (e.g. child of depressed mother). No study to date aimed to evaluate cognitive vulnerability of siblings of depressed individuals. Objectives: the present study aim to verify if siblings of depressed adolescents present a cognitive vulnerability that would predispose them to develop a major depression. Method: This study evaluates 49 adolescents (18 participants treated for depression, 16 siblings and 15 controls), aged between 12 and 20 years old. The cognitive vulnerability of every participant has been assessed using an auto-report questionnaire of symptoms (LEIDS-R) that evaluates cognitive reactivity and a task of facial recognition. Social cognition of participants is measured using the Movie for Assessment of Social Cognition (MASC) that we translated from german to french. Results: the preliminary analyses of this study concludes that a significant difference of cognitive reactivity is present between adolescents treated for depression and controls (p < 0.001). Conclusion: some of our results tend to confirm the presence of a cognitive vulnerability to depression among siblings of depressed adolescents. Those results are still preliminary and need to be confirmed by longitudinal studies.