COMPUTER
VISION
Funded Projects
The Research Foundation of CUNY
highlighted our NSF-sponsored project at its 2010 annual
report.
NSF CCF MSC (2009-2013)
($380,000)
Sequential
Classification and Detection via Markov Models in Point
Clouds of Urban Scenes
Description
One of the most important problems in 3D computer vision and
graphics is the automatic scene reconstruction from 2D and 3D
images. Recently, the reconstruction of complex urban scenes has
attracted significant interest. This is because accurate 3D city
models are paramount in the further development of a variety of
fields such as urban planning, architecture, and archeology. They
are also very important for applications commonly used in everyday
life such as street map visualization and navigation, as well as
in the film and construction industries. Automatic 3D image
reconstruction and classification of urban scenes, though, is a
problem whose complexity still challenges today's research
community. 3D reconstruction of city models is achieved through
data acquisition using a variety of devices such as laser scanners
and regular cameras. While laser scanners provide dense, detailed
and accurate 3D points, they suffer from slow speed which
dramatically increases the cost of acquisition. For more
information please go to link.
People
Co-PI
Ioannis
Stamos
Graduate Students
Hongzhong Zhang, Thomas Flynn
Undergraduate Students
Mansen Lin
Anh Dinh
Selected Relevant Publications
- "Sequential
Classification in Point Clouds of Urban Scenes",
O. Hadjiliadis and I. Stamos, Proceedings
of the 5th International
Symposium on 3D
Data Processing, Visualization and
Transmission, Paris,
France, May 17-20, 2010 [pdf].
- "Online
algorithms in the classification of urban objects in 3D
point clouds", I. Stamos, O.
Hadjiliadis, H. Zhang and T. Flynn, Proceedings of the 3D Imaging,
Modeling, Processing, Visualization and Transmission
(3DIMPVT) Conference, Zurich, Switzerland,
October 13-15, 2012
[pdf].
- "Trends
and trades", M. Carlisle, O.
Hadjiliadis and I. Stamos, Accepted for publication in
the Handbook of high-frequency trading and modeling in
finance. Editors: F. Viens, M. C. Mariani and I.
Florescu, Publisher: John Wiley and Sons (2014).
For a list of all publications click here
Related Internal Grants
- 2014: Gradual Change detection for object
classification in 3D Computer Vision, CUNY Collaborative,
$30,000, O. Hadjiliadis (PI), I. Stamos (co-PI).
NSF DMS IGMS (2009-2011)
($100,000)
Sequential Detection and
Classification in 3D Computer Vision
Description
The problem of quickest detection and classification in the
statistical behavior of sequential observations is a classical
one, with numerous applications in engineering, economics and
epidemiology. In today's fast-growing technologies new areas of
applications constantly emerge. In particular, the automatic 3D
image reconstruction and classification of urban scenes is a
problem whose complexity still challenges computer scientists. It
has traditionally been treated through the acquisition of data
using laser-scanners, which produce high-resolution images, but
can be very slow. It is thus essential to concentrate laser
scanning only to the areas of interest, which leads to fast
decision-making about areas of interest. This can save significant
time and cost, while still producing high-resolution 3D images.
The goal of this project is to develop and implement real-time
algorithms for processing and analyzing 3D laser range data. The
high-dimensional nature of the data is reduced by a clever
innovative selection of a measurement model. Interdependent
streams of observations are then processed by on-line parametric
and non-parametric classification and detection techniques. And
finally, new statistical models are used to capture obstacles in
urban scenes. This provides a systematic treatment of the problems
of fast and efficient 3D image classification using
high-resolution laser data. For more information please go to link.
People
Undergraduate Students
Artur Sahakyan
(Brooklyn College alumnus, currently employed at IBM's
dispatching division).
Selected
Relevant Publications
- "Sequential
Classification in Point Clouds of Urban Scenes",
O. Hadjiliadis and I. Stamos, Proceedings
of the 5th International
Symposium on 3D
Data Processing, Visualization and
Transmission, Paris,
France, May 17-20, 2010 [pdf].
- "Online
algorithms in the classification of urban objects in 3D
point clouds", I. Stamos, O.
Hadjiliadis, H. Zhang and T. Flynn, Proceedings of the 3D Imaging,
Modeling, Processing, Visualization and Transmission
(3DIMPVT) Conference, Zurich, Switzerland,
October 13-15, 2012
[pdf].
For a list of all publications click here