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PROF. GERD HÄUSLER   gerd.haeusler@physik.uni-erlangen.de   Telephon +49 9131 85 28382
 
 
  CURRENT RESEARCH
 
Flying Triangulation (FlyTri)
3D-Microscopy: Structured-Illumination Microscopy and Microdeflectometry
Potentials and Limitations of 3D Sensors
Phase-measuring deflectometry (PMD)
3D image processing
Medical Applications of Optical 3D-Sensors
There is a life beyond physics
   
 
 Flying Triangulation (FlyTri)
 

 
With Flying Triangulation we can measure the 3D topography of an object surface “on the fly”. Fields of application are twofold: On the one hand, measurements of complex or large objects such as sculptures or rooms, which require an excessive repositioning of the sensor. on the other hand, measurements of faces, teeth, or other body parts, where an uncontrolled motion of the object relative to the sensor is unavoidable.

FlyTri enables a motion-robust and freely hand-guided acquisition of objects by combining a simple sensor with complex algorithms. With a measurement uncertainty of 30 µm on a volume of measurement of 20 mm x 15 mm x 15 mm the sensor works at the physical limits. The sensor is scalable, from a measurement of teeth to an acquisition of large rooms.

 
further information:   http://www.optik.uni-erlangen.de/osmin/upload/flytri/videos/FlyTriTheMovieUT.mp4
   
related papers
 
Single-shot 3D sensing with improved data density | 2014
Robust pattern indexing methods for „Flying Triangulation“ | 2012
Medical Applications enabled by a motion-robust optical 3D sensor | 2012
Calibration of "Flying Traingulation" | 2012
Sparse Active Triangulation Grids for Respiratory Motion Management | 2012
Marker-less Reconstruction of Dense 4-D Surface Motion Fields using Active Laser Triangulation for Respiratory Motion Management | 2012
Options and limitations of "Flying Triangulation" | 2011
Optimized data processing for an optical 3D sensor based on Flying Triangulation | 2013
Hand – guided 3D surface acquisition by combining simple light sectioning with real-time algorithms | 2014
Flying Triangulation – Towards the 3D Movie Camera | 2014
Consequences of EEG electrode position error on ultimate beamformer source reconstruction performance | 2014
Management of head motion during MEG recordings with Flying Triangulation | 2013
Improved EEG source localization employing 3D sensing by "Flying Triangulation" | 2013
Joint Surface Reconstruction and 4-D Deformation Estimation from Sparse Data and Prior Knowledge for Marker-Less Respiratory Motion Tracking | 2013
Flying Triangulation - A Motion-Robust Optical 3D Sensor For The Real-Time Shape Acquisition Of Complex Objects | 2013
3D body scanning with "Flying Triangulation" | 2011
“Flying Triangulation”: A motion-robust optical 3D sensor principle | 2009
Detection and correction of line indexing ambiguities in Flying Triangulation | 2013
"Flying Triangulation" - a new optical 3D sensor enabling the acquisition of surfaces by freehand motion | 2009
A new registration method to robustly align a series of sparse 3D data | 2009
Flying triangulation—an optical 3D sensor for the motion-robust acquisition of complex objects | 2012
3D face scanning with "Flying Triangulation" | 2010
How precise is "Flying Triangulation" | 2010
"Flying Triangulation" – Acquiring the 360° Topography of the Human Body on the Fly | 2010
A 3D-Sensor for intraoral metrology | 2009
 
 
contact
 
 Dr. Svenja EttlTel: +49-9131-85-28385
 email: svenja.ettl@fau.de
 
 Dipl.-Phys. Florian WillomitzerTel: +49-9131-85-28381
 email: florian.willomitzer@physik.uni-erlangen.de
   
 
 3D-Microscopy: Structured-Illumination Microscopy and Microdeflectometry
 

 
We work on information-theoretically efficient full-field sensors for the inspection of technical surfaces with a depth sensitivity at the nanometer scale. The sensors use spatially and temporally incoherent illumination, are not based on interferometry and have no confocal pinholes.

Structured-Illumination Microscopy (SIM): A sinusoidal grating is projected in the focal plane of the microscope. By local contrast evaluation, SIM delivers the 3D-topography of smooth surfaces with a depth uncertainty of a few nanometers. At rough surfaces, the principally achievable uncertainty is determined by speckle noise and depends on the aperture (as in all triangulation systems).

Microdeflectometry (µPMD): A sinusoidal grating is projected by the micro-objective at a remote distance from the focal plane. The specular (smooth) object is located at the focal plane. A local tilt will cause a local phase shift of the grating mirror image. So this phase shift intrinsically encodes the local slope of the object. This unique feature makes the sensor the proper tool to measure local defects. Height variations in the order of one nanometer can be detected, with simple hardware.

Both sensors exploit the same technology, so they can easily be combined in one single microscope. The low noise, the high angular dynamic range, and the high depth of field allow for microscopic images with a quality similar to SEM images - with the further advantage to display quantitative 3D-data.

   
related papers
 
Structured-illumination microscopy on technical surfaces: 3D metrology with nanometer sensitivity | 2011
Full-field macroscopic measurement of specular, curved surfaces with SIM | 2011
Fast acquisition of 3D-data with Structured Illumination Microscopy | 2011
Microdeflectometry and Structured Illumination Microscopy – New Tools for 3D-Metrology at Nanometer Scale | 2010
Tuning Structured Illumination Microscopy (SIM) for the Inspection of Micro Optical Components | 2010
Information efficient and accurate Structured Illumination Microscopy (SIM) | 2010
3D-microscopy with large depth of field | 2009
Microdeflectometry in transmission | 2009
Microdeflectometry—a novel tool to acquire three-dimensional microtopography with nanometer height resolution | 2008
 
 
contact
 
 M. Sc. Zheng YangTel: +49-9131-85-28384
 email: zheng.yang@physik.uni-erlangen.de
   
 
 Potentials and Limitations of 3D Sensors
 

 
Optical 3D-sensors can measure the distance of stars and the thickness of atomic layers. How many sensors do we need to cover that range of about 24 orders of magnitude? It is interesting that there are only three physically different physical principles of signal formation, and we principally need only three "types of sensors" (we do not consider nonlinear light-matter interaction). We distinguish the signal formation in terms of how the physically unavoidable noise of the measured shape data scales with the distance. It turns out that all triangulation sensors such as laser triangulation, fringe projection, stereo vision or focus sensors are limited by speckle noise. The physical measuring uncertainty scales with the square of the stand off distance. This is the reason why laser triangulation cannot compete with mechanical touch probes. In classical interferometry the major source of noise is quantum noise. The physical measuring uncertainty scales with the inverse stand off distance (surprised?). A completely different mechanism of signal generation occurs in broad band interferometry on optically rough surfaces. Due to the nonlinear mixing of different object frequencies, we are able to measure the surface roughness beyond the Abbe limit. The physical measuring uncertainty does not depend on sensor parameters such as apertures or stand off, it depends only on the roughness of the object surface.

   
related papers
 
Three-Dimensional Sensors - Potentials and Limitations | 1999
Information theoretical optimization for optical range sensors | 2003
How much may a 3d-sensor cost? - a sincere scientific question | 2003
3D sensor zoo – Species and natural habitats | 2006
Limitations of optical 3D sensors | 2011
Why can´t we purchase a perfect single shot 3D sensor? | 2012
Ubiquitous coherence – boon and bale of the optical metrologist | 2003
 
 
contact
 
 Prof. Gerd HäuslerTel: +49-9131-85-28382
 email: haeusler@physik.uni-erlangen.de
 
 Dipl.-Phys. Florian WillomitzerTel: +49-9131-85-28381
 email: florian.willomitzer@physik.uni-erlangen.de
   
 
 Phase-measuring deflectometry (PMD)
 

 
With phase-measuring deflectometry we are able to measure the slope - and by numerical integration the topography - of reflecting surfaces. We project fringes on a ground glass screen and observe the pattern, using the object as a mirror. Any slope deviations of the object lead to distortions of the fringe pattern observed by the camera.
To calculate the local curvature of aspheric lenses, we measure the slope of the surface and calculate the first derivative. This process is much less noise sensitive than the evaluation from shape data. The image on the right shows the surface astigmatism of a progressive eyeglass lens, measured with PMD. The curvature maps have an accuracy of better than 0.02D calculated on an area of only 3x3mm².
The method is scalable from large objects like painted car bodies or windscreens, over eyeglass lenses and wafers down to microlenses.

   
related papers
 
Deflectometric measurement of large mirrors | 2014
Deflectometry: 3D-Metrology from Nanometer to Meter | 2009
Deflektometrie macht der Interferometrie Konkurrenz | 2009
Can deflectometry work in presence of parasitic reflections? | 2009
Object tilt - a source of systematic error in transmission deflectometry | 2009
Deflectometry vs. interferometry | 2013
New Holistic Self-Calibration Method for Deflectometric Sensors | 2010
Object reconstruction by deflectometry | 2012
Deflectometry for Ultra Precision Machining - Measuring without Rechucking | 2011
Deflektometrische Selbstkalibrierung für spiegelnde Objekte | 2011
Deflectometry challenges interferometry: the competition gets tougher! | 2012
Machine-Integrated Measurement of Specular Free-Formed Surfaces Using Phase-Measuring Deflectometry | 2009
Generalized Hermite interpolation with radial basis functions considering only gradient data | 2007
Phasenmessende Deflektometrie | 2009
Microdeflectometry in transmission | 2009
Measuring the refractive power with deflectometry in transmission | 2008
Sub-micron profilometry on macroscopic free-form surfaces | 2008
Microdeflectometry—a novel tool to acquire three-dimensional microtopography with nanometer height resolution | 2008
Shape reconstruction from gradient data | 2008
Zauberspiegel, Brillengläser und Wasserhähne - alte Probleme neu beleuchtet | 2007
Fast and robust 3D shape reconstruction from gradient data | 2007
Höhe, Neigung oder Krümmung? | 2006
Shape reconstruction of 3d-objects from noisy slope data | 2005
Vision and Modeling of Specular Surfaces | 2005
Full-Field Shape Measurement of Specular Surfaces | 2005
Absolute Phase Measuring Deflectometry | 2004
Absolute Phasenmessende Deflektometrie | 2004
Richtungscodierte Deflektometrie | 2004
Phase Measuring Deflectometry: a new approach to measure specular free-form surfaces | 2004
Measurement of Eye Glasses with Phase Measuring Deflectometry | 2003
Calculating curvatures from discrete slope data | 2003
Metric Calibration of "Phase Measuring Deflectometry" | 2002
Reaching the Physical Limits of Phase Measuring Deflectometry | 2002
Phase Measuring Deflectometry - Simulation of the Sensor | 2001
Physical limits of phase mesuring deflectometry | 2001
Phase Measuring Deflectometry - a new method to measure reflecting surfaces | 2000
 
 
contact
 
 Dipl.-Math. Evelyn OleschTel: +49-9131-85-28384
 email: evelyn.olesch@physik.uni-erlangen.de
   
 
 3D image processing
 

 
The goal of this subproject is to create a system of (already existing) 3d sensors and (new) algorithms for automatically digitizing the complete surface of a three-dimensional object together with its color information. Range and color images will be acquired from different viewpoints, registered in a common coordinate system, and merged into a single textured, polyhedral surface description with minimal or even no user interaction at all.

Further, we exploit the reconstruction of an object's surface from its local slope data. The objects under test are free-form objects having a specular surface, such as for example eyeglass lenses, wafers, solar cells, coated car bodies, ...
The slope data is aquired by the sensor based on phase-measuring deflectometry (PMD) developed in our group. Applying these methods we can achieve a sensitivity in the nanometer range and a global shape accuracy in the micrometer range.

   
related papers
 
Shape reconstruction from gradient data | 2008
Fast and robust 3D shape reconstruction from gradient data | 2007
How to localize 3D-views in space? | 2005
Segmentation Based Fast Registration of Free Form Surfaces in the Euclidean Space | 2006
Automatic Coarse Registration of 3D-Surfaces by Information Theoretic Selection of Salient Points | 2006
Automatic registration method for multisensor datasets adopted for dimensional measurements on cutting tools | 2013
Full-Field Shape Measurement of Specular Surfaces | 2005
Optimized data processing for an optical 3D sensor based on Flying Triangulation | 2013
Robust automatic coarse registration of specular free-form surfaces | 2007
Vision and Modeling of Specular Surfaces | 2005
Consequences of EEG electrode position error on ultimate beamformer source reconstruction performance | 2014
Marker-less Reconstruction of Dense 4-D Surface Motion Fields using Active Laser Triangulation for Respiratory Motion Management | 2012
Management of head motion during MEG recordings with Flying Triangulation | 2013
Automatic Coarse Registration of 3D Surfaces | 2005
Automatic Coarse Registration of 3D Surface Data in Oral and Maxillofacial Surgery | 2004
Fast Automatic Registration of Varying 3D Surface Data in Oral and Maxillofacial Surgery | 2004
Informationsoptimierte Merkmale zur Grobregistrierung von Freiform-Flächen | 2004
Three dimensional acquisition of colored objects | 2002
A Sub-Atomic Subdivision Approach | 2001
Localization and registration of three-dimensional objects in space - where are the limits ? | 2001
Refining Triangle Meshes by Non-Linear Subdivision | 2001
Processing Range Data for Reverse Engineering and Virtual Reality | 2001
Fusion of discrete Models | 2000
Discrete Modeling of Point Clouds | 2000
Feature Extraction and Registration | 2000
Polygon Meshes | 2000
Illumination estimation | 2000
Digitizing 3D objects for reverse engineering and virtual reality | 2000
A Non-linear Subdivision Scheme for Triangle Meshes | 2000
 
 
contact
 
 Dr. Svenja EttlTel: +49-9131-85-28385
 email: svenja.ettl@fau.de
   
 
 Medical Applications of Optical 3D-Sensors
 

 
There is a wide range of applications of optical 3D sensors in the medical field.

One goal is to intraoperatively support the surgeon during the repair of a displacement of the globe of the eye. To date, the surgeon has to evaluate his operation result solely by visual judgement. Our idea is to intraoperatively provide the surgeon a comparison between the actual 3D position of the globe and its nominal position. The actual state is obtained by an intraoperative 3D measurement of the patient's face with an optical 3D sensor. The nominal result is computed based on a preoperative measurement of the patient with the same sensor. Our main assumption for the computation of the nominal eye position is that the ideal face is symmetrical. Thus, knowing the symmetry plane of the patients face the mirrored 3D position of the undamaged globe defines the nominal position for the displaced globe of the eye.

The other goal is to enable a multi-modal coregistration of medical data with the aid of optical 3D sensors. This way, not only the required time demand can be reduced immensely, but also the precision can be increased.

   
related papers
 
Fast Automatic Registration of Varying 3D Surface Data in Oral and Maxillofacial Surgery | 2004
Medical Applications enabled by a motion-robust optical 3D sensor | 2012
Automatische Segmentierung der Gewebegrenzen in 2D-Ultraschalldaten aus der Mund-, Kiefer- und Gesichtschirurgie | 2006
Weichgewebemodellierung durch Flächeninterpolation heterogen verteilter Messdaten | 2006
Optical 3d-metrology for medical applications | 2005
Quantitative Comparison of Facial Soft Tissue Surfaces | 2004
Sparse Active Triangulation Grids for Respiratory Motion Management | 2012
Joint Surface Reconstruction and 4-D Deformation Estimation from Sparse Data and Prior Knowledge for Marker-Less Respiratory Motion Tracking | 2013
Improved EEG source localization employing 3D sensing by "Flying Triangulation" | 2013
Management of head motion during MEG recordings with Flying Triangulation | 2013
Marker-less Reconstruction of Dense 4-D Surface Motion Fields using Active Laser Triangulation for Respiratory Motion Management | 2012
Consequences of EEG electrode position error on ultimate beamformer source reconstruction performance | 2014
Symmetry of faces | 2001
The Symmetry of Faces | 2002
Automatic Coarse Registration of Optical 3D Data in Oral and Maxillofacial Surgery | 2003
Automatische Grobregistrierung intraoperativ akquirierter 3D-Daten von Gesichtsoberflächen anhand ihrer Gauß'schen Abbilder | 2003
Automatic Coarse Registration of 3D Surface Data in Oral and Maxillofacial Surgery | 2004
 
 
contact
 
 Dr. Svenja EttlTel: +49-9131-85-28385
 email: svenja.ettl@fau.de
   
 
 There is a life beyond physics
 

 
Observations about scientists life and all that.

 
further information:   http://www.optik.uni-erlangen.de/osmin/upload/pdf/GH_2013_SPIE_Porto_Research_Entrepreneurschip.pdf
   
related papers
 
Two adventures for six scientists | 2001
Funding, Bureaucracy and All That | 2002
 
 
contact
 
 Prof. Gerd HäuslerTel: +49-9131-85-28382
 email: haeusler@physik.uni-erlangen.de
   
 
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