Automatic Extraction of Planar Projections
from Panoramic Range Images
Abstract
This paper presents a segmentation technique to
decompose automatically a panoramic range image into
a set of planar projections. It consists of three stages.
Firstly, two orthogonal surface orientation histograms
are generated. Secondly, from these histograms the major
surfaces’ orientations are extracted. Finally, a histogram
of distances is computed for each one of these orienta-
tions; it will be used to define the position of the
projection planes as well as the corresponding clipping
planes. The original panoramic range image is divided
into as many planar projections as main directions in the
orientation histograms are extracted. This technique can
be used with both indoor and outdoor scenes. Experimen-
tal result with a panoramic range image is presented.
1. Introduction
During the past years 3D computer vision has experi-
enced a fast growth. The appearance of new sensors,
which allow the obtainment of a huge amount of three-
dimensional information in a short time, and the need to
process and represent these images efficiently, has given
rise to new research topics in the 3D computer vision
community. One of these topics is the 3D digital repre-
sentation that has gained an important place in different
fields (e.g. architectural [1], [2], [3], automotive engi-
neering [4], robotics [5], computer animations [6], to
mention a few). However, the gap existing between 3D
digital representations and the classical planar drawings
need to be saved—considering that planar drawings are
the “de facto” representations for many applications.
Planar drawings are still nowadays used because of
their portability. In industrial environments or building
works is not easy to find the appropriate tools to visualize
or show 3D digital representations. In this sense, this
paper presents a technique to generate automatically pla-
nar projections from 3D panoramic images. Up to our
knowledge, [7] is one of the first works taking the prob-
lem of panoramic range image decomposition. In [7],
panoramic range images of forest scenes have been inves-
tigated. In the current work indoor and outdoor scenes,
scanned by using the Imager 530 scanner, developed by
the Z+F company, have been tested. This sensor allows a
scanning rate up to 625,000 points per second with a pan-
oramic field of view in the horizontal direction and a field
of view of 135 degrees in the vertical direction (more
technical details about the Imager 530 scanner are given
at the company’s Web page: www.zf-uk.com).
The Imager 530 scanner allows capturing the full
geometry of big environments, with a high fidelity, in a
short time. The required space to store all this information
(images bigger than 500MB) or the CPU power to process
all these data are not a problem for the current technol-
ogy. The only constrain for these panoramic range images
appears when it is necessary to print or represent all these
3D data in a single snapshot. The envisaged solution is
the segmentation of the original panoramic range image
into a set of easy to understand planar representations.
Planar drawings can be used not only as a final repre-
sentation but they can also be used to define the next
position of the sensor. This problem, known in the litera-
ture as the next-best-view problem [5][8], consists in
computing the positions where the range sensor should be
placed in order to acquire the surfaces of the objects
present in a scene minimizing the total amount of scans.
The computed planar representations can be used to
detect occluded areas or low resolution areas, defining
thus the next position of the sensor.
The proposed technique consists of three stages.
Firstly, two surface orientation histograms are computed;
they will unveil the major surfaces’ orientations of the
given panoramic scene. Secondly, main directions are
extracted by combining local maximum from the previous
The author has been supported by The Ramón y Cajal Program
Angel D. Sappa
Computer Vison Center
Edifici O, Campus UAB
08193 Bellaterra - Barcelona, Spain
angel.sappa@cvc.uab.es
Proceedings of the 2nd Intl Symp 3D Data Processing, Visualization, and Transmission (3DPVT 2004)
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