Eyewitnesses’ Visual Recollection in Suspect Identification by using Facial Appearance Model

يعتبر تمييز الوجه مجالًا نشطًا لعلوم التصوير. ومع التطورات الحديثة في تطوير رؤية الكمبيوتر ، يتم تطبيقه على نطاق واسع في مختلف المجالات ، وخاصة في فرض القانون والأمن. ان الوجه البشري مقياس حيوي يمكن استخدامه بفعالية في كل من تحديد الهوية والتحقق منها. حتى الآن ، وبغض النظر عن نموذج الوجه والمقاييس ذات الصلة المستخدمة ، فإن عيبه الرئيس هو أنه يتطلب صورة للوجه ، يتم إجراء المقارنة عليها. لذلك ، هناك حاجة دائمًا إلى أجهزة تلفزيون الدائرة المغلقة وقاعدة بيانات الوجه في نظام التشغيل. وللأسف خلال العقود القليلة الماضية ، شهدنا ظهور حرب غير متكافئة ، حيث يتم ارتكاب أعمال إرهابية في كثير من الأحيان في منطقة منعزلة بدون كاميرا مثبتة وربما بواسطة أشخاص لم يتم حفظ صورهم في أي قاعدة بيانات رسمية قبل الحدث. خلال التحقيقات اللاحقة ، كان على السلطات بالتالي الاعتماد على شهود مصابين بصدمات نفسية واحباط ، وهؤلاء تعتبر شهادتهم مشكوك فيها وغالبًا ما تكون مضللة بشأن ظهور المشتبه فيه. لمعالجة هذه المشكلة ، تقدم هذه الورقة تطبيقًا لنموذج المظهر الإحصائي للوجه الإنساني في المساعدة على تحديد هوية المشتبه به استنادًا إلى التذكر البصري للشاهد. تم تنفيذ نظام نموذج أولي عبر الإنترنت لإظهار وظائفه الأساسية. أشار كل من التقييمات المرئية والعددية الواردة هنا بشكل واضح إلى الفوائد المحتملة للنظام للغرض المقصود.Facial recognition has been an active field of imaging science. With the recent progresses in computer vision development, it is extensively applied in various areas, especially in law enforcement and security. Human face is a viable biometric that could be effectively used in both identification and verification. Thus far, regardless of a facial model and relevant metrics employed, its main shortcoming is that it requires a facial image, against which comparison is made. Therefore, closed circuit televisions and a facial database are always needed in an operational system. For the last few decades, unfortunately, we have experienced an emergence of asymmetric warfare, where acts of terrorism are often committed in secluded area with no camera installed and possibly by persons whose photos have never been kept in any official database prior to the event. During subsequent investigations, the authorities thus had to rely on traumatized and frustrated witnesses, whose testimonial accounts regarding suspect’s appearance are dubious and often misleading. To address this issue, this paper presents an application of a statistical appearance model of human face in assisting suspect identification based on witness’s visual recollection. An online prototype system was implemented to demonstrate its core functionalities. Both visual and numerical assessments reported herein evidentially indicated potential benefits of the system for the intended purpose

Integrating 3D Objects and Pose Estimation for Multimodal Video Annotations

With the recent technological advancements, using video has become a focal point on many ubiquitous activities, from presenting ideas to our peers to studying specific events or even simply storing relevant video clips. As a result, taking or making notes can become an invaluable tool in this process by helping us to retain knowledge, document information, or simply reason about recorded contents. This thesis introduces new features for a pre-existing Web-Based multimodal anno- tation tool, namely the integration of 3D components in the current system and pose estimation algorithms aimed at the moving elements in the multimedia content. There- fore, the 3D developments will allow the user to experience a more immersive interaction with the tool by being able to visualize 3D objects either in a neutral or 360º background to then use them as traditional annotations. Afterwards, mechanisms for successfully integrating these 3D models on the currently loaded video will be explored, along with a detailed overview of the use of keypoints (pose estimation) to highlight details in this same setting. The goal of this thesis will thus be the development and evaluation of these features seeking the construction of a virtual environment in which a user can successfully work on a video by combining different types of annotations.Ao longo dos anos, a utilização de video tornou-se um aspecto fundamental em várias das atividades realizadas no quotidiano como seja em demonstrações e apresentações profissionais, para a análise minuciosa de detalhes visuais ou até simplesmente para preservar videos considerados relevantes. Deste modo, o uso de anotações no decorrer destes processos e semelhantes, constitui um fator de elevada importância ao melhorar potencialmente a nossa compreensão relativa aos conteúdos em causa e também a ajudar a reter características importantes ou a documentar informação pertinente. Efetivamente, nesta tese pretende-se introduzir novas funcionalidades para uma fer- ramenta de anotação multimodal, nomeadamente, a integração de componentes 3D no sistema atual e algorítmos de Pose Estimation com vista à deteção de elementos em mo- vimento em video. Assim, com estas features procura-se proporcionar um experiência mais imersiva ao utilizador ao permitir, por exemplo, a visualização preliminar de objec- tos num plano tridimensional em fundos neutros ou até 360º antes de os utilizar como elementos de anotação tradicionais. Com efeito, serão explorados mecanismos para a integração eficiente destes modelos 3D em video juntamente com o uso de keypoints (pose estimation) permitindo acentuar pormenores neste ambiente de visualização. O objetivo desta tese será, assim, o desenvol- vimento e avaliação continuada destas funcionalidades de modo a potenciar o seu uso em ambientes virtuais em simultaneo com as diferentes tipos de anotações já existentes

Online and Distance Learning during Lockdown Times

This book is a reprint of papers in the Special Issue published in Education Sciences under the title "Online and Distance Learning during Lockdown Times: COVID-19 Stories". It includes papers covering Higher Education (post-secondary) sector representing international experience of teaching and learning from the start of the first episode of lockdown due to the Covid-19 pandemic