Coupling ground-level panoramas and aerial imagery for change detection

International audienceGeographic landscapes in all over the world may be subject to rapid changes induced, for instance, by urban, forest, and agricultural evolutions. Monitoring such kind of changes is usually achieved through remote sensing. However, obtaining regular and up-to-date aerial or satellite images is found to be a high costly process, thus preventing regular updating of land cover maps. Alternatively, in this paper, we propose a low-cost solution based on the use of ground-level geo-located landscape panoramic photos providing high spatial resolution information of the scene. Such photos can be acquired from various sources: digital cameras, smartphone, or even web repositories. Furthermore, since the acquisition is performed at the ground level, the users' immediate surroundings, as sensed by a camera device, can provide information at a very high level of precision, enabling to update the land cover type of the geographic area. In the described herein method, we propose to use inverse perspective mapping (inverse warping) to transform the geo-tagged ground-level 360 • photo onto a top-down view as if it had been acquired from a nadiral aerial view. Once re-projected, the warped photo is compared to a previously acquired remotely sensed image using standard techniques such as correlation. Wide differences in orientation, resolution, and geographical extent between the top-down view and the aerial image are addressed through specific processing steps (e.g. registration). Experiments on publicly available data-sets made of both ground-level photos and aerial images show promising results for updating land cover maps with mobile technologies. Finally, the proposed approach contributes to the crowdsourcing efforts in geo-information processing and mapping, providing hints on the evolution of a landscape. ARTICLE HISTOR

Mobile Augmented Reality in Museums : Towards Enhancing Visitor's Learning Experience

This article presents the design and implementation of a handheld Augmented Reality (AR) system called Mobile Augmented Reality Touring System (M.A.R.T.S). The results of experiments conducted during museum visits using this system are also described. These experiments aim at studying how such a tool can transform the visitor’s learning experience by comparing it to two widely used museum systems. First, we present the museum’s learning experience and a related model which emerged from the state of the art. This model consists of two types of activity experienced by the observer of a work of art: sensitive and analytical. Then, we detail M.A.R.T.S architecture and implementation. Our empirical study highlights the fact that AR can direct visitors’ attention by emphasizing and superimposing. Its magnifying and sensitive effects are well perceived and appreciated by visitors. The obtained results reveal that M.A.R.T.S contributes to a worthwhile learning experience

Towards a unified framework for identity documents analysis and recognition

Identity documents recognition is far beyond classical optical character recognition problems. Automated ID document recognition systems are tasked not only with the extraction of editable and transferable data but with performing identity validation and preventing fraud, with an increasingly high cost of error. A significant amount of research is directed to the creation of ID analysis systems with a specific focus for a subset of document types, or a particular mode of image acquisition, however, one of the challenges of the modern world is an increasing demand for identity document recognition from a wide variety of image sources, such as scans, photos, or video frames, as well as in a variety of virtually uncontrolled capturing conditions. In this paper, we describe the scope and context of identity document analysis and recognition problem and its challenges; analyze the existing works on implementing ID document recognition systems; and set a task to construct a unified framework for identity document recognition, which would be applicable for different types of image sources and capturing conditions, as well as scalable enough to support large number of identity document types. The aim of the presented framework is to serve as a basis for developing new methods and algorithms for ID document recognition, as well as for far more heavy challenges of identity document forensics, fully automated personal authentication and fraud prevention.This work was partially supported by the Russian Foundation for Basic Research (Project No. 18-29-03085 and 19-29-09055)

Ingénierie de la conception de systèmes de réalité augmentée mobile. Applications de la réalité augmentée mobile au tourisme culturel

Le système M.A.R. T.S a été conçu avec l'objectif de proposer un nouveau mode de médiation au musée. Lorsque la visite au musée se déroule sans guide conférencier, les outils de médiation classiques comme l'audio-guide ou les étiquettes montrent rapidement leurs limites en termes d'interaction humaine. Nous proposons donc de permettre au visiteur d'interagir avec un guide humain virtuel appuyé de nos paradigmes d'interaction " Sélection Documentation Reconstruction", puisant leurs principes de la réalité augmentée. L'objectif, par le biais de nos propositions, est de créer les conditions propices à un contact riche avec la collection, et de donner au visiteur les outils nécessaires pour qu'il puisse vivre une expérience d'apprentissage riche au musée. Les expérimentations que nous avons menées vont dans ce sens, montrant l'efficacité de ce nouveau mode de médiation. Qui plus est, les principes d'interactions sont suffisamment généraux pour dépasser le cadre original de la visite guidée au musée et peuvent être exploitée pour une visite guidée à l'extérieur.M.A.R.T.S system was built in order to propose a new mode of museum mediation. When the museum visit take place without a human guide, classical mediation tools such as labels or audio-guide rapidly show their limits in terms of human interaction. We therefore propose to allow visitors to interact with a virtual human guide supported by our interaction paradigms "Selection Documentation Reconstruction", which are based on augmented reality. The aim behind our proposals is to ensure favorable conditions for a rich contact with collections, and provide the visitor with necessary tools enabling him to live a worthwhile learning experience in the museum. The experiments we have conducted go in this direction, showing the effectiveness of this new mode of museum mediation. Moreover, interactions principles are sufficiently general to be applied to other cultural heritage activities such as outdoor guided tours

Semi-structured document image matching and recognition

International audienceThis article presents a method to recognize and to localize semi-structured documents such as ID cards, tickets, invoices, etc. Object recognition methods based on interest points work well on natural images but fail on document images because of repetitive patterns like text. In this article, we propose an adaptation of object recognition for image documents. The advantages of our method is that it does not use character recognition or segmentation and it is robust to rotation, scale, illumination, blur, noise and local distortions. Furthermore, tests show that an average precision of 97.2% and recall of 94.6% is obtained for matching 7 di erent kinds of documents in a database of 2155 documents