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I have an official AAU profile here:
http://personprofil.aau.dk/Profil/101384
I am working with 3D reconstruction of peach trees in californian peach fields for automatic thinning of peach blossoms.
I am also working with Games For Health such as multimodal interactive games for exercise, accesiblity and rehabilitation.
I have also worked with model based shadow segmentation. I designed a penumbra model based on
the illumination theory of Graham Finlayson. I estimate parameters via Kolmogorov's graph cut framework.
I teach and supervise in fields like program design, programming, computer vision, multimodal interaction, etc.
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Publications:
A PROCEDURE FOR DEVELOPING
INTUITIVE AND ERGONOMIC GESTURE INTERFACES FOR MAN-MACHINE
INTERACTION
Michael Nielsen, Thomas Moeslund, Moritz Störring, Erik
Granum
Technical Report, CVMT 03-01, ISSN 1601-3646, 2003
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A PROCEDURE FOR DEVELOPING
INTUITIVE AND ERGONOMIC GESTURE INTERFACES FOR HCI
Michael Nielsen, Thomas Moeslund, Moritz Störring, Erik
Granum
In proceedings Gesture-Based Communication in
Human-Computer Interaction
5th International Gesture
Workshop, GW 2003, Genova, Italy, April 15-17, 2003, Selected
Revised Papers, pp 409
Springer
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SUB-LEAF SCALE REMOTE
SENSOR FOR NPK DISCRIMINATION USING STEREO VISION
Michael
Nielsen, Lene K. Christensen, Hans Jørgen
Andersen.
AgEng 2004, Leuven, Belgium,
12-16 September, 2004
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DETECTING LEAF FEATURES FOR AUTOMATIC WEED CONTROL USING
TRINOCULAR STEREO VISION
Michael Nielsen, H.J.
Andersen
,
D.C.
Slaughter and D.K.
Giles.
International Conference on
Precision Agriculture, July 2004, Minneapolis, MN, USA
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Ground Truth Evaluation of 3D
Computer Vision on Non-Rigid Biological Structures
Michael Nielsen, Hans J.
Andersen, David C. Slaughter, Erik Granum
In Precision Agriculture
‘05 (Ed. John Stafford), Proceedings from ECPA, June,
2005,
pp 549-556, Wageningen Academic Publishers, The
Netherlands
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Comparative Study of Disparity
Estimations with Multi-Camera Configurations in Relation to
Descriptive Parameters of Complex Biological Objects
Michael Nielsen, Hans J.
Andersen, Erik Granum
BenCOS - Towards Benchmarking
Automated Calibration, Orientation and Surface Reconstruction
from Images. ISPRS Workshop in conjunction with ICCV 2005,
pp 63-68,
Beijing, October, 2005
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Shadow Segmentation and Augmentation Using á-overlay Models that Account for Penumbra
Michael Nielsen and Claus B. Madsen
Proceedings fra den 15. Danske Konference i Mønstergenkendelse og Billedanalyse.
DIKU Technical Report No. 06/08, 2006. s. 60-69, København, Danmark, 24. august 2006 - 25. august 2006.
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Work:
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CoSPE
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Computer vision based Scene Parameter Estimation
The project aims at estimating light source and material properties, i.e., illumination conditions and reflectances, given an image or a sequence of images of a scene.
My part is to estimate an alpha-layer which describes the effect of shadow for each pixel in an image.
www.cospe.dk
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FG-Net
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Face- and Gesture
Network.
FGnet is the European working group
on face and gesture recognition funded by the E.C.IST program.The
objectives of FGnet are to of encourage development of a
technology for face and gesture recognition. The network goals
are:
(1) to assist development face and gesture
recognition technology
(2) to create a set of foresight reports
defining development roadmaps and future use scenarios for the
technology in the medium (5-7 years) and long (10-20 years)
term
(3) to specify, develop and supply
resources (eg image sets) supporting these
scenarios
This web site is maintained by FGnet as a
tool for internal communication and as a means of providing
information and results to the larger scientific
community.
http://www.cvmt.dk/~fgnet/
During this work I have developed some Image Recording and
Annotation tools that are available on the Tools page.
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ACROSS
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Autonomous spatial-temporal
Crop and Soil Surveying
The general vision is effective precision farming, which in
harmony with the environment utilises resources optimally. This
requires continuous selective and adaptive control of growth,
weeds, diseases and pest. In turn such control is conditioned on
corresponding continuous monitoring in the field using
appropriate methods of measuring the current conditions of and
for the plant growth.
The objective of this project is to develop methods of measuring
and managing such information to support the above vision in a
way that invites also new innovative approaches to precision
farming by providing the necessary information on demand and in
time for planning and decision making.
More concretely the project will develop methods and technology
for:
Computer vision methods for on-site and real-time monitoring of
information of the crop growth (nutrients, diseases, etc.). The
methods will allow diagnostics of crop condition based on
reflection patterns (e.g. mis-coloured areas) down to single leaf
scale.
Implementation and integration of the above methods on an
autonomous platform with a suite of existing crop and soil
measuring facilities for on-site operation
Repeated test and evaluation for development and Proof of
concept: “Autonomous Crop and Soil Surveillance”
Hence the project through new research and practical development
will contribute to a new scope precision agriculture, which until
now has not been seen in its full perspectives, due to the lack
of precise and timely information
http://www.cvmt.dk/projects/Across/index.html
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