Augmented reality interaction and vision-based tracking

Master'sMASTER OF ENGINEERIN

Keyframe Tagging: Unambiguous Content Delivery for Augmented Reality Environments

Context: When considering the use of Augmented Reality to provide navigation cues in a completely unknown environment, the content must be delivered into the environment with a repeatable level of accuracy such that the navigation cues can be understood and interpreted correctly by the user. Aims: This thesis aims to investigate whether a still image based reconstruction of an Augmented Reality environment can be used to develop a content delivery system that providers a repeatable level of accuracy for content placement. It will also investigate whether manipulation of the properties of a Spatial Marker object is sufficient to reduce object selection ambiguity in an Augmented Reality environment. Methods: A series of experiments were conducted to test the separate aspects of these aims. Participants were required to use the developed Keyframe Tagging tool to introduce virtual navigation markers into an Augmented Reality environment, and also to identify objects within an Augmented Reality environment that was signposted using different Virtual Spatial Markers. This tested the accuracy and repeatability of content placement of the approach, while also testing participants’ ability to reliably interpret virtual signposts within an Augmented Reality environment. Finally the Keyframe Tagging tool was tested by an expert user against a pre-existing solution to evaluate the time savings offered by this approach against the overall accuracy of content placement. Results: The average accuracy score for content placement across 20 participants was 64%, categorised as “Good” when compared with an expert benchmark result, while no tags were considered “incorrect” and only 8 from 200 tags were considered to have “Poor” accuracy, supporting the Keyframe Tagging approach. In terms of object identification from virtual cues, some of the predicted cognitive links between virtual marker property and target object did not surface, though participants reliably identified the correct objects across several trials. Conclusions: This thesis has demonstrated that accurate content delivery can be achieved through the use of a still image based reconstruction of an Augmented Reality environment. By using the Keyframe Tagging approach, content can be placed quickly and with a sufficient level of accuracy to demonstrate its utility in the scenarios outlined within this thesis. There are some observable limitations to the approach, which are discussed with the proposals for further work in this area

A feature-based approach for monocular camera tracking in unknown environments

© 2017 IEEE. Camera tracking is an important issue in many computer vision and robotics applications, such as, augmented reality and Simultaneous Localization And Mapping (SLAM). In this paper, a feature-based technique for monocular camera tracking is proposed. The proposed approach is based on tracking a set of sparse features, which are successively tracked in a stream of video frames. In the developed system, camera initially views a chessboard with known cell size for few frames to be enabled to construct initial map of the environment. Thereafter, Camera pose estimation for each new incoming frame is carried out in a framework that is merely working with a set of visible natural landmarks. Estimation of 6-DOF camera pose parameters is performed using a particle filter. Moreover, recovering depth of newly detected landmarks, a linear triangulation method is used. The proposed method is applied on real world videos and positioning error of the camera pose is less than 3 cm in average that indicates effectiveness and accuracy of the proposed method

Applying Augmented Reality to Outdoors Industrial Use

Augmented Reality (AR) is currently gaining popularity in multiple different fields. However, the technology for AR still requires development in both hardware and software when considering industrial use. In order to create immersive AR applications, more accurate pose estimation techniques to define virtual camera location are required. The algorithms for pose estimation often require a lot of processing power, which makes robust pose estimation a difficult task when using mobile devices or designated AR tools. The difficulties are even larger in outdoor scenarios where the environment can vary a lot and is often unprepared for AR. This thesis aims to research different possibilities for creating AR applications for outdoor environments. Both hardware and software solutions are considered, but the focus is more on software. The majority of the thesis focuses on different visual pose estimation and tracking techniques for natural features. During the thesis, multiple different solutions were tested for outdoor AR. One commercial AR SDK was tested, and three different custom software solutions were developed for an Android tablet. The custom software solutions were an algorithm for combining data from magnetometer and a gyroscope, a natural feature tracker and a tracker based on panorama images. The tracker based on panorama images was implemented based on an existing scientific publication, and the presented tracker was further developed by integrating it to Unity 3D and adding a possibility for augmenting content. This thesis concludes that AR is very close to becoming a usable tool for professional use. The commercial solutions currently available are not yet ready for creating tools for professional use, but especially for different visualization tasks some custom solutions are capable of achieving a required robustness. The panorama tracker implemented in this thesis seems like a promising tool for robust pose estimation in unprepared outdoor environments.Lisätyn todellisuuden suosio on tällä hetkellä kasvamassa usealla eri alalla. Saatavilla olevat ohjelmistot sekä laitteet eivät vielä riitä lisätyn todellisuuden soveltamiseen ammattimaisessa käytössä. Erityisesti posen estimointi vaatii tarkempia menetelmiä, jotta immersiivisten lisätyn todellisuuden sovellusten kehittäminen olisi mahdollista. Posen estimointiin (laitteen asennon- sekä paikan arviointiin) käytetyt algoritmit ovat usein monimutkaisia, joten ne vaativat merkittävästi laskentatehoa. Laskentatehon vaatimukset ovat usein haasteellisia varsinkin mobiililaitteita sekä lisätyn todellisuuden laitteita käytettäessä. Lisäongelmia tuottaa myös ulkotilat, jossa ympäristö voi muuttua usein ja ympäristöä ei ole valmisteltu lisätyn todellisuuden sovelluksille. Diplomityön tarkoituksena on tutkia mahdollisuuksia lisätyn todellisuuden sovellusten kehittämiseen ulkotiloihin. Sekä laitteisto- että ohjelmistopohjaisia ratkaisuja käsitellään. Ohjelmistopohjaisia ratkaisuja käsitellään työssä laitteistopohjaisia ratkaisuja laajemmin. Suurin osa diplomityöstä keskittyy erilaisiin visuaalisiin posen estimointi tekniikoihin, jotka perustuvat kuvasta tunnistettujen luonnollisten piirteiden seurantaan. Työn aikana testattiin useita ratkaisuja ulkotiloihin soveltuvaan lisättyyn todellisuuteen. Yhtä kaupallista työkalua testattiin, jonka lisäksi toteutettiin kolme omaa sovellusta Android tableteille. Työn aikana kehitetyt sovellukset olivat yksinkertainen algoritmi gyroskoopin ja magnetometrin datan yhdistämiseen, luonnollisen piirteiden seuranta-algoritmi sekä panoraamakuvaan perustuva seuranta-algoritmi. Panoraamakuvaan perustuva seuranta-algoritmi on toteuteutettu toisen tieteellisen julkaisun pohjalta, ja algoritmia jatkokehitettiin integroimalla se Unity 3D:hen. Unity 3D-integrointi mahdollisti myös sisällön esittämisen lisätyn todellisuuden avulla. Työn lopputuloksena todetaan, että lisätyn todellisuuden teknologia on lähellä pistettä, jossa lisätyn todellisuuden työkaluja voitaisiin käyttää ammattimaisessa käytössä. Tällä hetkellä saatavilla olevat kaupalliset työkalut eivät vielä pääse ammattikäytön vaatimalle tasolle, mutta erityisesti visualisointitehtäviin soveltuvia ei-kaupallisia ratkaisuja on jo olemassa. Lisäksi työn aikana toteutetun panoraamakuviin perustuvan seuranta-algoritmin todetaan olevan lupaava työkalu posen estimointiin ulkotiloissa.Siirretty Doriast

Combining Image Processing Techniques and Mobile Sensor Information for Marker-less Augmented Reality Based Reconstruction

Marker-less Augmented Reality(AR) based recon- struction using mobile devices, is a near impossible task. When considering vision based tracking approaches, it is due to the lack of processing power in mobile devices and when considering mobile sensor based tracking approaches, it is due to the lack of accuracy in mobile Global Positioning System(GPS). In order to address this problem this research presents a novel approach which combines image processing techniques and mobile sensor information which can be used to perform precise position localization in order to perform augmented reality based reconstruction using mobile devices. The core of this proposed methodology is tightly bound with the image processing technique which is used to identify the object scale in a given image, which is taken from the user’s mobile device. Use of mobile sensor information was to classify the most optimal locations for a given particular user location. This proposed methodology has been evaluated against the results obtained using 10cm accurate Real-Time Kinematic(RTK) device and against the results obtained using only the Assisted Global  Positioning  System(A-GPS)  chips  in  mobile  devices. Though  this  proposed  methodology  require  more  processing time than A-GPS chips, the accuracy level of this proposed methodology outperforms that of A-GPS chips and the results of the experiments carried out further convince that this proposed methodology facilitates improving the accuracy of position local- ization for augmented reality based reconstruction using mobile devices under certain limitations

Cultural Heritage in Marker-Less Augmented Reality: A Survey

Augmented Reality (AR) is considered as one of the most significant technologies in the field of computer graphics and is utilized for many applications. In this paper, we have presented a comprehensive survey for cultural heritage using Augmented Reality systems. This survey describes the main objectives and characteristics of Marker-less Augmented Reality Systems through presenting up-to-date research results in this area. We describe the marker-less technologies in the area of AR, indoor marker-less AR, outdoor marker-less AR, real-time solutions to the tracking problem, real-time registration, cultural heritage in AR, 3D remonstration techniques, as well as presenting the problems in each research