Enabling post-recording deep georeferencing of walkthrough videos : an interactive apprach

Dissertation submitted in partial fulfilment of the requirements for the degree of Master of Science in Geospatial TechnologiesThe usage of large scale databases of georeferenced video stream has an in nite number of applications in industry and research since e cient storing in geodatabases to allowing the performing of spatial queries. Due to the fact that the video capturing devices have become ubiquitous, a good source for the acquisition of a lot of video contents is the crowdsourced approach of Social Media. However, these social apps usually do not support geo metadata or it is very limited to a single location on Earth. In other cases, the regular user usually does not have the required hardware and software to capture video footage with a deep georeference (position and orientation in time). There is a clear lack of methods for the extraction of that spatial component in video footage. This study proposes and evaluates a new method for the manual capture and extraction of the spatial geo-reference in the post production phase of video content. The proposed framework is based on a map-based user interface synchronized with the video stream. The e ciency and usability of the resulting framework were evaluated performing a user study, in addition, the resulting geo-metadata of the manual extracted georeference has been compared with the one previously captured by hardware in order to evaluate the goodness of the method

Subjective and objective quality evaluation of synthetic and high dynamic range images

Recent years have seen a huge growth in the acquisition, transmission, and storage of videos. The visual data consists of both natural scenes as well as synthetic scenes, such as animated movies, cartoons and video games. In all these cases, the ultimate goal is to provide the viewers with a satisfactory quality-of-experience. In addition to the traditional 8-bit images, high dynamic range imaging is also becoming popular because of its ability to represent the real world luminances more realistically. Coming up with objective image quality assessment algorithms for these applications is an interesting research problem. In this work, I have developed a synthetic image quality database by introducing varying degrees of different types of distortions and conducted a subjective experiment in order to obtain the ground-truth data. I evaluated the performance of state-of-the-art image quality assessment algorithms (typically meant for natural images) on this database, especially no-reference algorithms that have not been applied to the domain of computer graphics images before. I identified the top-performing algorithms along with analyzing the types of distortions on which the present algorithms show a less impressive performance. For high dynamic range(HDR) images, I have designed two new full-reference image quality assessment algorithms to judge the quality of tonemapped HDR images using statistical features extracted from them. I have also conducted a massive online crowd-sourced subjective test for HDR image artifacts arising from tonemapping, multiple-exposure fusion and post processing. To the best of our knowledge, presently this is the largest HDR image database in the world involving the largest number of source images and most number of human evaluations. Based on the subjective evaluations obtained, I have also proposed machine learning based no-reference image quality assessment algorithms to predict the perceptual quality of HDR images.Electrical and Computer Engineerin

Enabling post-recording deep georferencing of walkthrough videos : an interactive approach

Màster Universitari en Tecnologia Geoespacial/Geospatial Technologies. Codi: SIK013. Curs: 2015/2016The usage of large scale databases of georeferenced video stream has an infinite number of applications in industry and research since efficient storing in geodatabases to allowing the performing of spatial queries. Due to the fact that the video capturing devices have become ubiquitous, a good source for the acquisition of a lot of video contents is the crowdsourced approach of Social Media. However, these social apps usually do not support geo metadata or it is very limited to a single location on Earth. In other cases, the regular user usually does not have the required hardware and software to capture video footage with a deep georeference (position and orientation in time). There is a clear lack of methods for the extraction of that spatial component in video footage. This study proposes and evaluates a new method for the manual capture and extraction of the spatial geo-reference in the post production phase of video content. The proposed framework is based on a map-based user interface synchronized with the video stream. The efficiency and usability of the resulting framework were evaluated performing a user study, in addition, the resulting geo-metadata of the manual extracted georeference has been compared with the one previously captured by hardware in order to evaluate the goodness of the method

INNUENDO: A cross-sectoral platform for the integration of genomics in the surveillance of food-borne pathogens

Abstract In response to the EFSA call New approaches in identifying and characterizing microbial and chemical hazards, the project INNUENDO (https://sites.google.com/site/theinnuendoproject/) aimed to design an analytical platform and standard procedures for the use of whole-genome sequencing in surveillance and outbreak investigation of food-borne pathogens. The project firstly attempted to identify existing flaws and needs, and then to provide applicable cross-sectorial solutions. The project focused in developing a platform for small countries with limited economical and personnel resources. To achieve these goals, we applied a user-centered design strategy involving the end-users, such as microbiologists in public health and veterinary authorities, in every step of the design, development and implementation phases. As a result, we delivered the INNUENDO Platform V1.0 (https://innuendo.readthedocs.io/en/latest/), a stand-alone, portable, open-source, end-to-end system for the management, analysis, and sharing of bacterial genomic data. The platform uses Nextflow workflow manager to assemble analytical software modules in species-specific protocols that can be run using a user-friendly interface. The reproducibility of the process is ensured by using Docker containers and throught the annotation of the whole process using an ontology. Several modules, available at https://github.com/TheInnuendoProject, have been developed including: genome assembly and species confirmation; fast genome clustering; in silico typing; standardized species-specific phylogenetic frameworks for Campylobacter jejuni, Yersinia enterocolitica, Salmonella enterica and Escherichia coli based on an innovative gene-by-gene methodology; quality control measures from raw reads to allele calling; reporting system; a built-in communication protocols and a strain classification system enabling smooth communication during outbreak investigation. As proof-of-concepts, the proposed solutions have been thoroughly tested in simulated outbreak conditions by several public health and veterinary agencies across Europe. The results have been widely disseminated through several channels (web-sites, scientific publications, organization of workshops). The INNUENDO Platform V1.0 is effectively one of the models for the usage of open-source software in genomic epidemiology.Peer reviewe

Challenges for engineering students working with authentic complex problems

Engineers are important participants in solving societal, environmental and technical problems. However, due to an increasing complexity in relation to these problems new interdisciplinary competences are needed in engineering. Instead of students working with monodisciplinary problems, a situation where students work with authentic complex problems in interdisciplinary teams together with a company may scaffold development of new competences. The question is: What are the challenges for students structuring the work on authentic interdisciplinary problems? This study explores a three-day event where 7 students from Aalborg University (AAU) from four different faculties and one student from University College North Denmark (UCN), (6th-10th semester), worked in two groups at a large Danish company, solving authentic complex problems. The event was structured as a Hackathon where the students for three days worked with problem identification, problem analysis and finalizing with a pitch competition presenting their findings. During the event the students had workshops to support the work and they had the opportunity to use employees from the company as facilitators. It was an extracurricular activity during the summer holiday season. The methodology used for data collection was qualitative both in terms of observations and participants’ reflection reports. The students were observed during the whole event. Findings from this part of a larger study indicated, that students experience inability to transfer and transform project competences from their previous disciplinary experiences to an interdisciplinary setting

Exploring the practical use of a collaborative robot for academic purposes

This article presents a set of experiences related to the setup and exploration of potential educational uses of a collaborative robot (cobot). The basic principles that have guided the work carried out have been three. First and foremost, study of all the functionalities offered by the robot and exploration of its potential academic uses both in subjects focused on industrial robotics and in subjects of related disciplines (automation, communications, computer vision). Second, achieve the total integration of the cobot at the laboratory, seeking not only independent uses of it but also seeking for applications (laboratory practices) in which the cobot interacts with some of the other devices already existing at the laboratory (other industrial robots and a flexible manufacturing system). Third, reuse of some available components and minimization of the number and associated cost of required new components. The experiences, carried out following a project-based learning methodology under the framework of bachelor and master subjects and thesis, have focused on the integration of mechanical, electronic and programming aspects in new design solutions (end effector, cooperative workspace, artificial vision system integration) and case studies (advanced task programming, cybersecure communication, remote access). These experiences have consolidated the students' acquisition of skills in the transition to professional life by having the close collaboration of the university faculty with the experts of the robotics company.Postprint (published version