Selecting surface features for accurate multi-camera surface reconstruction

This paper proposes a novel feature detector for selecting local textures that are suitable for accurate multi-camera surface reconstruction, and in particular planar patch fitting techniques. This approach is in contrast to conventional feature detectors, which focus on repeatability under scale and affine transformations rather than suitability for multi-camera reconstruction techniques. The proposed detector selects local textures that are sensitive to affine transformations, which is a fundamental requirement for accurate patch fitting. The proposed detector is evaluated against the SIFT detector on a synthetic dataset and the fitted patches are compared against ground truth. The experiments show that patches originating from the proposed detector are fitted more accurately to the visible surfaces than those originating from SIFT keypoints. In addition, the detector is evaluated on a performance capture studio dataset to show the real-world application of the proposed detector

Selecting surface features for accurate multi-camera surface reconstruction

This paper proposes a novel feature detector for selecting local textures that are suitable for accurate multi-camera surface reconstruction, and in particular planar patch fitting techniques. This approach is in contrast to conventional feature detectors, which focus on repeatability under scale and affine transformations rather than suitability for multi-camera reconstruction techniques. The proposed detector selects local textures that are sensitive to affine transformations, which is a fundamental requirement for accurate patch fitting. The proposed detector is evaluated against the SIFT detector on a synthetic dataset and the fitted patches are compared against ground truth. The experiments show that patches originating from the proposed detector are fitted more accurately to the visible surfaces than those originating from SIFT keypoints. In addition, the detector is evaluated on a performance capture studio dataset to show the real-world application of the proposed detector

A Survey on Augmented Reality Challenges and Tracking

This survey paper presents a classification of different challenges and tracking techniques in the field of augmented reality. The challenges in augmented reality are categorized into performance challenges, alignment challenges, interaction challenges, mobility/portability challenges and visualization challenges. Augmented reality tracking techniques are mainly divided into sensor-based tracking, visionbased tracking and hybrid tracking. The sensor-based tracking is further divided into optical tracking, magnetic tracking, acoustic tracking, inertial tracking or any combination of these to form hybrid sensors tracking. Similarly, the vision-based tracking is divided into marker-based tracking and markerless tracking. Each tracking technique has its advantages and limitations. Hybrid tracking provides a robust and accurate tracking but it involves financial and tehnical difficulties

Enhanced Concrete Bridge Assessment Using Artificial Intelligence and Mixed Reality

Conventional methods for visual assessment of civil infrastructures have certain limitations, such as subjectivity of the collected data, long inspection time, and high cost of labor. Although some new technologies (i.e. robotic techniques) that are currently in practice can collect objective, quantified data, the inspector\u27s own expertise is still critical in many instances since these technologies are not designed to work interactively with human inspector. This study aims to create a smart, human-centered method that offers significant contributions to infrastructure inspection, maintenance, management practice, and safety for the bridge owners. By developing a smart Mixed Reality (MR) framework, which can be integrated into a wearable holographic headset device, a bridge inspector, for example, can automatically analyze a certain defect such as a crack that he or she sees on an element, display its dimension information in real-time along with the condition state. Such systems can potentially decrease the time and cost of infrastructure inspections by accelerating essential tasks of the inspector such as defect measurement, condition assessment and data processing to management systems. The human centered artificial intelligence (AI) will help the inspector collect more quantified and objective data while incorporating inspector\u27s professional judgment. This study explains in detail the described system and related methodologies of implementing attention guided semi-supervised deep learning into mixed reality technology, which interacts with the human inspector during assessment. Thereby, the inspector and the AI will collaborate/communicate for improved visual inspection

Herramientas de desarrollo libres para aplicaciones de realidad aumentada con Android. Análisis comparativo entre ellas

[ES] Estudio de las herramientas existentes para el desarrollo de aplicaciones de RA para dispositivos móviles con sistema operativo Android e identificación de ventajas e inconvenientes entre ellas.[EN] Study of existing frameworks for AR applications development for Android mobile devices and identification of strengths and weaknesses among them.Serrano Mamolar, A. (2012). Herramientas de desarrollo libres para aplicaciones de realidad aumentada con Android. Análisis comparativo entre ellas. http://hdl.handle.net/10251/18028Archivo delegad

Markerless Augmented Reality with a Real-time Affine Region Tracker

We present a system for planar augmented reality based on a new real-time affine region tracker. Instead of tracking fiducial points, we track planar local image patches, and bring these into complete correspondence, so a virtual texture can directly be added to them. Moreover, the local image patches can be extracted in an invariant way, even without any a priori information from previous frames. Hence it is possible to use them as natural beacons, that can be used to recognize the scene and to identify the individual patches. This results in a powerful system, that can work without artificial markers or fiducial points and with a minimal amount of user interference

Corrección del error en el proceso de registro en los sistemas de realidad aumentada utilizando técnicas heurísticas

Desde la masificación de los primeros computadores en la década de los 90’s su uso estaba restringido a desarrollar tareas específicas y cálculos repetitivos. En la actualidad, los computadores y sistemas informáticos están permeando cada vez más las actividades humanas, convirtiéndose en lo que Weiser define como Sistemas Ubicuos [Wei99]. Este nuevo paradigma de interacción humano-máquina implica disponer de interfaces naturales que permitan una comunicación efectiva entre el usuario y la máquina, presentando grandes retos para las ciencias de la computación en cuanto al diseño de sistemas, su modelamiento y, en particular, el desarrollo de las interfaces de usuario. En este contexto, las interfaces deben entrar en consonancia con el concepto de Amplificación de la Inteligencia [Bro96][Bro96a] tal que permita la creación de sistemas capaces de amplificar o mejorar las capaces cognitivas humanas en lugar de imitarlas o reemplazarlas. En esta búsqueda de interfaces cada vez más naturales que extiendan las capacidades perceptivas humanas, surge la creación de nuevos entornos y metáforas de visualización como la Realidad Virtual (RV) y la Realidad Aumentada (RA). En particular, la realidad aumentada aparece como un nuevo paradigma de visualización e interacción humano-máquina que permite al usuario obtener información adicional (información virtual) de su entorno e incluso manipular esta información conservando su relación con el ambiente real. La obtención de dicha información adicional, se logra mediante la superposición en el ambiente real, de información virtual generada por computador. La creación de un sistema de realidad aumentada involucra varias etapas, a saber: calibración de dispositivos, extracción de características, seguimiento y registro. Esta última etapa presenta grandes retos para la creación de un ambiente de RA realista, ya que aquí se une tanto la información virtual como la real; si dicha alineación no es correcta, el sistema será visualmente incoherente. Es por esto que el registro es una etapa crítica que actualmente limita las aplicaciones de realidad aumentada. En la presente tesis, se aborda por medio de técnicas heurísticas esta limitación, que ha sido recurrente en la literatura. Como aporte se propone el uso de técnicas heurísticas, las cuales hasta ahora no han sido abordadas en la literatura, para disminuir el error existente entre la información de posicionamiento obtenida en etapas anteriores al proceso de registro (información estimada) y la información real. Dicha disminución en el error se traduce en un alineamiento real-virtual (etapa de registro) mucho más preciso y coherente, obteniendo en consecuencia sistemas o ambientes que apoyen de manera efectiva los problemas de visualización y acceso a información en una mayor cantidad de aplicaciones./Abstarct. Since the first computers appear in the early 90’s, its use was restricted to perform specific tasks and repetitive calculations. Today, computers are getting mixed in human activities more and more, becoming what Weiser [Wei99] defined as ubiquitous systems. This new paradigm of human-machine interaction implies the availability of natural interfaces that allow an effective communication between the user and the machine. It presents great challenges for computer science related to the systems design and modeling, and in particular, the development of user interfaces. In this context, the interfaces must be in relation with the concept of Intelligence Amplification [Bro96][Bro96a], that allows the creation of systems that can amplify or improve human cognitive perceptions rather than imitate or replace them. In this search for more and more natural interfaces that extend human cognitive capacities, new environments and visualization metaphors such as Virtual Reality (VR) and Augmented Reality (AR) rose. In particular, augmented reality appears as a new paradigm for visualization and human-machine interaction that allows the user to obtain additional information (virtual information) from his/her environment and even manipulate this information while preserving their relationship with the real world. Obtaining such information is achieved by the overlap in the real environment, virtual information generated by computer. The creation of an augmented reality system involves several steps, namely, device calibration, feature extraction, tracking and registration. This last stage presents great challenges for creating an realistic AR environment, since this stage binds both the virtual and the real information, if the alignment is not correct, the system will be visually incoherent. This is why the registration is a critical stage which currently limits the applications of augmented reality. In this thesis, this limitation is tackle by means of heuristics. Contributions include the use of heuristics to reduce the error between the position information obtained in previous stages to the registration process (information estimated) and real data. This reduction in error resulting in a real-virtual alignment (registration stage) much more accurate and consistent, thus gaining support to systems and environments to solve effectively visualization problems and access to information in a larger number of applications.Maestrí