Adaptable Model-Based Tracking Using Analysis-by-Synthesis Techniques

Wuest, Harald; Wientapper, Folker; Stricker, Didier

doi:10.1007/978-3-540-74272-2_3

Cited by 20 publications

(12 citation statements)

References 10 publications

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“…The proposed approach makes it possible to use all tracking methods on all devices, independent of the processing capabilities of the mobile devices. In our Augmented Reality framework InstantVision [3], the available markerless camera tracking technologies encompass (amongst others) point-based and edge-based camera tracking [25], model-based analysis-by-synthesis methods [26], the reconstruction and alignment of 3D feature maps [23] as well as visual-inertial structure from motion [5] [6]. Furthermore the tracking and initialization methods comprise BAG of visual words [7] [13] and HIPs [20].…”

Section: Mobile Camera Trackingmentioning

confidence: 99%

Beyond 3D "As-Built" Information Using Mobile AR Enhancing the Building Lifecycle Management

Kahn

Olbrich

Engelke

et al. 2012

2012 International Conference on Cyberworlds

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The success of smartphone technologies changed the way information is processed as more and more geo-referenced structures are emerging linking information to specific locations within our environment. Thereby, Augmented Reality has become a key technology as it analyses the smartphone sensor data (camera, GPS, inertial) to derive the detailed pose of the smartphone, with the aim to correlate our real environment to the geo-referenced information space. In particular, this is relevant for application fields where 3D-models are used in planning and organization processes as e.g. facility management. In facility construction and management Building Information Model (BIM) was established as a standard that not only holds the 3D-building-geometry but encompasses pipe/electrical systems as well as semantic building information, for example properties and conditions of building components. With this motivation our work integrates BIM and Augmented Reality.

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Section: Mobile Camera Trackingmentioning

confidence: 99%

Beyond 3D "As-Built" Information Using Mobile AR Enhancing the Building Lifecycle Management

Kahn

Olbrich

Engelke

et al. 2012

2012 International Conference on Cyberworlds

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“…(Behringer et al, 2002), (Reitmayr and Drummond, 2006) and (Simon, 2011) need additional sensors for position (GPS) and orientation to initialize their tracking systems in large outdoor environments. (Wuest et al, 2007) propose the use of an inertial measurement unit in the future for initialization. (Ulrich et al, 2009) use offline training of various possible object poses to achieve an image based initialization.…”

Section: Previous Researchmentioning

confidence: 99%

“…5). This approach is called analysis-by-synthesis (Wuest et al, 2007). The idea is, to render a view of the 3D model, extract all visible edges from it and match them to the real camera image of the model.…”

Section: Renderingmentioning

confidence: 99%

Self-Localization of a Multi-Fisheye Camera Based Augmented Reality System in Textureless 3d Building Models

Urban

Leitloff

Wursthorn

et al. 2013

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:Georeferenced images help planners to compare and document the progress of underground construction sites. As underground positioning can not rely on GPS/GNSS, we introduce a solely vision based localization method, that makes use of a textureless 3D CAD model of the construction site. In our analysis-by-synthesis approach, depth and normal fisheye images are rendered from presampled positions and gradient orientations are extracted to build a high dimensional synthetic feature space. Acquired camera images are then matched to those features by using a robust distance metric and fast nearest neighbor search. In this manner, initial poses can be obtained on a laptop in real-time using concurrent processing and the graphics processing unit.

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“…Where appropriate, the initial model estimation by computer vision algorithms comprises a fourth element (Koch, 1993). Typical application examples for analysis-by-synthesis include camera calibration (Eisert, 2002;Koeser et al, 2007;Wuest et al, 2007), human motion analysis (Moeslund et al, 2006) and (object) tracking applications (Hasler et al, 2007). A similar concept is used in medical applications for 2d-3d image registration with digitally reconstructed radiographs (DRR) (Penney et al, 1998).…”

Section: Analysis-by-synthesis and Materials Appearancementioning

confidence: 99%

Enhanced anomaly detection in wire ropes by combining structure and appearance

Wacker

Denzler

2013

Pattern Recognition Letters

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Automatic visual surface inspection is a challenging task, which has become important for quality assurance in the last years. Wire rope inspection is a special problem within this field. Usually, the huge and heavy ropes cannot be detached. Thus, an inspection of the ropes must be conducted, while the ropes are in use. The rope surface exhibits various appearance characteristics so that the existing, purely appearance-based approaches tend to fail.We explicitly integrate information about the object geometry, which we obtain by aligning a sequence of 2d rope images with a perfectly regular 3d model of the rope. The rendering equation is used to link object geometry to the observed rope appearance. Based on the connection between geometry and surface appearance we build a probabilistic appearance model which serves as representation for normal surface variations. A robust localization of rope surface defects is achieved by means of anomaly detection. The presented approach has no need for knowledge about the illumination setting or the reflectance properties of the material.An evaluation on real-world data from ropeways leads to an accuracy comparable to that of a human expert. With an accuracy of 95% and a false-alarm-rate of 1.5% the approach outperforms all other existing approaches.

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Adaptable Model-Based Tracking Using Analysis-by-Synthesis Techniques

Cited by 20 publications

References 10 publications

Beyond 3D "As-Built" Information Using Mobile AR Enhancing the Building Lifecycle Management

Beyond 3D "As-Built" Information Using Mobile AR Enhancing the Building Lifecycle Management

Self-Localization of a Multi-Fisheye Camera Based Augmented Reality System in Textureless 3d Building Models

Enhanced anomaly detection in wire ropes by combining structure and appearance

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