Adaptive Vision Based Scene Registration for Outdoor Augmented Reality

Augmented Reality (AR) involves adding virtual content into real scenes. Scenes are viewed using a Head-Mounted Display or other display type. In order to place content into the user's view of a scene, the user's position and orientation relative to the scene, commonly referred to as their pose, must be determined accurately. This allows the objects to be placed in the correct positions and to remain there when the user moves or the scene changes. It is achieved by tracking the user in relation to their environment using a variety of technology. One technology which has proven to provide accurate results is computer vision. Computer vision involves a computer analysing images and achieving an understanding of them. This may be locating objects such as faces in the images, or in the case of AR, determining the pose of the user. One of the ultimate goals of AR systems is to be capable of operating under any condition. For example, a computer vision system must be robust under a range of different scene types, and under unpredictable environmental conditions due to variable illumination and weather. The majority of existing literature tests algorithms under the assumption of ideal or 'normal' imaging conditions. To ensure robustness under as many circumstances as possible it is also important to evaluate the systems under adverse conditions. This thesis seeks to analyse the effects that variable illumination has on computer vision algorithms. To enable this analysis, test data is required to isolate weather and illumination effects, without other factors such as changes in viewpoint that would bias the results. A new dataset is presented which also allows controlled viewpoint differences in the presence of weather and illumination changes. This is achieved by capturing video from a camera undergoing a repeatable motion sequence. Ground truth data is stored per frame allowing images from the same position under differing environmental conditions, to be easily extracted from the videos. An in depth analysis of six detection algorithms and five matching techniques demonstrates the impact that non-uniform illumination changes can have on vision algorithms. Specifically, shadows can degrade performance and reduce confidence in the system, decrease reliability, or even completely prevent successful operation. An investigation into approaches to improve performance yields techniques that can help reduce the impact of shadows. A novel algorithm is presented that merges reference data captured at different times, resulting in reference data with minimal shadow effects. This can significantly improve performance and reliability when operating on images containing shadow effects. These advances improve the robustness of computer vision systems and extend the range of conditions in which they can operate. This can increase the usefulness of the algorithms and the AR systems that employ them

Seamless Positioning and Navigation in Urban Environment

L'abstract è presente nell'allegato / the abstract is in the attachmen

Forum Bildverarbeitung 2016

Bildverarbeitung spielt in vielen Bereichen der Technik zur schnellen und berührungslosen Datenerfassung eine Schlüsselrolle. Der vorliegende Tagungsband des „Forums Bildverarbeitung“, das am 1. und 2. Dezember 2016 in Karlsruhe als Veranstaltung des Karlsruher Instituts für Technologie und des Fraunhofer-Instituts für Optronik, Systemtechnik und Bildauswertung stattfand, enthält die Aufsätze der eingegangenen Beiträge. Darin wird über aktuelle Trends und Lösungen der Bildverarbeitung berichtet

Context-aware gestural interaction in the smart environments of the ubiquitous computing era

A thesis submitted to the University of Bedfordshire in partial fulfilment of the requirements for the degree of Doctor of PhilosophyTechnology is becoming pervasive and the current interfaces are not adequate for the interaction with the smart environments of the ubiquitous computing era. Recently, researchers have started to address this issue introducing the concept of natural user interface, which is mainly based on gestural interactions. Many issues are still open in this emerging domain and, in particular, there is a lack of common guidelines for coherent implementation of gestural interfaces. This research investigates gestural interactions between humans and smart environments. It proposes a novel framework for the high-level organization of the context information. The framework is conceived to provide the support for a novel approach using functional gestures to reduce the gesture ambiguity and the number of gestures in taxonomies and improve the usability. In order to validate this framework, a proof-of-concept has been developed. A prototype has been developed by implementing a novel method for the view-invariant recognition of deictic and dynamic gestures. Tests have been conducted to assess the gesture recognition accuracy and the usability of the interfaces developed following the proposed framework. The results show that the method provides optimal gesture recognition from very different view-points whilst the usability tests have yielded high scores. Further investigation on the context information has been performed tackling the problem of user status. It is intended as human activity and a technique based on an innovative application of electromyography is proposed. The tests show that the proposed technique has achieved good activity recognition accuracy. The context is treated also as system status. In ubiquitous computing, the system can adopt different paradigms: wearable, environmental and pervasive. A novel paradigm, called synergistic paradigm, is presented combining the advantages of the wearable and environmental paradigms. Moreover, it augments the interaction possibilities of the user and ensures better gesture recognition accuracy than with the other paradigms

UAVs for the Environmental Sciences

This book gives an overview of the usage of UAVs in environmental sciences covering technical basics, data acquisition with different sensors, data processing schemes and illustrating various examples of application

Ricerche di Geomatica 2011

Questo volume raccoglie gli articoli che hanno partecipato al Premio AUTeC 2011. Il premio è stato istituito nel 2005. Viene conferito ogni anno ad una tesi di Dottorato giudicata particolarmente significativa sui temi di pertinenza del SSD ICAR/06 (Topografia e Cartografia) nei diversi Dottorati attivi in Italia

Towards observable haptics: Novel sensors for capturing tactile interaction patterns

Kõiva R. Towards observable haptics: Novel sensors for capturing tactile interaction patterns. Bielefeld: Bielefeld University; 2014.Touch is one of the primary senses humans use when performing coordinated interaction, but the lack of a sense of touch in the majority of contemporary interactive technical systems, such as robots, which operate in non-deterministic environments, results in interactions that can at best be described as clumsy. Observing human haptics and extracting the salient information from the gathered data is not only relevant if we are to try to understand the involved underlying cognitive processes, but should also provide us with significant clues to design future intelligent interactive systems. Such systems could one day help to take the burden of tedious tasks off our hands in a similar fashion to how industrial robots revolutionized manufacturing. The aim of the work in this thesis was to provide significant advancements in tactile sensing technology, and thus move us a step closer to realizing this goal. The contributions contained herein can be broken into two major parts. The first part investigates capturing interaction patterns in humans with the goals of better understanding manual intelligence and improving the lives of hand amputees, while the second part is focused on augmenting technical systems with a sense of touch. tacTiles, a wireless tactile sensitive surface element attached to a deformable textile, was developed to capture human full-body interactions with large surfaces we come into contact with in our daily lives, such as floors, chairs, sofas or other furniture. The Tactile Dataglove, iObject and the Tactile Pen were developed especially to observe human manual intelligence. Whereas iObject allows motion sensing and a higher definition tactile signal to be captured than the Tactile Dataglove (220 tactile cells in the first iObject prototype versus 54 cells in the glove), the wearable glove makes haptic interactions with arbitrary objects observable. The Tactile Pen was designed to measure grip force during handwriting in order to better facilitate therapeutic treatment assessments. These sensors have already been extensively used by various research groups, including our own, to gain a better understanding of human manual intelligence. The Finger-Force-Linear-Sensor and the Tactile Bracelet are two novel sensors that were developed to facilitate more natural control of dexterous multi Degree-of-Freedom (DOF) hand prostheses. The Finger-Force-Linear-Sensor is a very accurate bidirectional single finger force ground-truth measurement device that was designed to enable testing and development of single finger forces and muscle activations mapping algorithms. The Tactile Bracelet was designed with the goal to provide a more robust and intuitive means of control for multi-DOF hand prostheses by measuring the muscle bulgings of the remnant muscles of lower arm amputees. It is currently in development and will eventually cover the complete forearm circumference with high spatial resolution tactile sensitive surfaces. An experiment involving a large number of lower arm amputees has already been planned. The Modular flat tactile sensor system, the Fabric-based touch sensitive artificial skin and the 3D shaped tactile sensor were developed to cover and to add touch sensing capabilities to the surfaces of technical systems. The rapid augmentation of systems with a sense of touch was the main goal of the modular flat tactile sensor system. The developed sensor modules can be used alone or in an array to form larger tactile sensitive surfaces such as tactile sensitive tabletops. As many robots have curved surfaces, using flat rigid modules severely limits the areas that can be covered with tactile sensors. The Fabric-based tactile sensor, originally developed to form a tactile dataglove for human hands, can with minor modifications also function as an artificial skin for technical systems. Finally, the 3D shaped tactile sensor based on Laser-Direct-Structuring technology is a novel tactile sensor that has a true 3D shape and provides high sensitivity and a high spatial resolution. These sensors take us further along the path towards creating general purpose technical systems that in time can be of great help to us in our daily lives. The desired tactile sensor characteristics differ significantly according to which haptic interaction patterns we wish to measure. Large tactile sensor arrays that are used to capture full body haptic interactions with floors and upholstered furniture, or that are designed to cover large areas of technical system surfaces, need to be scalable, have low power consumption and should ideally have a low material cost. Two examples of such sensors are tacTiles and the Fabric-based sensor for curved surfaces. At the other end of the tactile sensor development spectrum, if we want to observe manual interactions, high spatial and temporal resolution are crucial to enable the measurement of fine grasping and manipulation actions. Our fingertips contain the highest density area of mechanoreceptors, the organs that sense mechanical pressure and distortions. Thus, to construct biologically inspired anthropomorphic robotic hands, the artificial tactile sensors for the fingertips require similar high-fidelity sensors with surfaces that are curved under small bending radii in 2 dimensions, have high spatial densities, while simultaneously providing high sensitivity. With the fingertip tactile sensor, designed to fit the Shadow Robot Hands' fingers, I show that such sensors can indeed be constructed in the 3D-shaped high spatial resolution tactile sensor section of my thesis. With my work I have made a significant contribution towards making haptics more observable. I achieved this by developing a high number of novel tactile sensors that are usable, give a deeper insight into human haptic interactions, have great potential to help amputees and that make technical systems, such as robots, more capable