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International Archives of the Photogrammetry, Remote Sensing
Surprisingly, some manufactures of lasers scanners discard
some information generated by their scanners. All optical
three-dimensional (3D) scanners measure the reflectance
information generated by the intensity of the returned laser
beam but in many cases, the manufacturer eliminates that
important information from the raw 3D image file. In an
inspection application, El-Hakim et al. 1994 show that the use
of intensity data (reflectance) produced by a range camera can
improve the accuracy of vision-based 3D measurements. The
authors provide a survey (pre-1994) of multi-sensor data fusion
methods in the context of computer vision.
Wendt et al. 2002 present an approach for data fusion and
simultaneous adjustment of inhomogeneous data intended to
increase the accuracy and reliability of surface reconstruction.
They aimed at an approach to adjust any kind of data in a
combined adjustment and to give adequate weights to each
measurement. Their study is based on 3D data obtained from
stripe (fringe) projection and photogrammetry-based systems.
To validate their approach, they use two types of free-form
object surfaces, one being artificial and known is used for test
purposes and the other is a tile made of concrete. Johnson et al.,
2002 describe a technique for adaptive resolution surface
generation from multiple distributed sensors. They demonstrate
the technique using 3D data generated by a scanning lidar and a
structure from motion system. Other authors compare and
discuss practicality issues of laser scanning and digital close
range photogrammetry (Velios et al, 2002; CIPA&ISPRS,
2002). Increasingly, laser scanning and photogrammetry are
combined for many applications. These applications include
documentation of as-built sites like offshore oil and gas
structures, process plants, nuclear and power generation
stations, architectural and construction sites, industrial
manufacturing facilities, automotive production, space
exploration and cultural heritage.
In this paper, resolution, uncertainty and accuracy of 3D
information measurement in the context of close-range 3D
Systems are discussed. Laser scanners are reviewed in more
details compared to photogrammetry. A number of examples
illustrating the importance of sensor characterization are shown.
Some comments about the impact of a user in a project are also
presented. The goal is not to survey all commercial 3D vision
Systems or present an exhaustive list of tests of the systems
chosen for this paper. Instead, some basic theory about 3D
sensing is presented and is accompanied by selected results that
should give the reader some pointers in order to become more
critical when picking 3D vision systems and a sensor fusion
strategy.
2. OPTICAL SENSORS FOR THREE-DIMENSIONAL
MEASUREMENTS
In the last twenty years, many advances have been made in the
field of solid-state electronics, photonics, computer vision and
computer graphics. Non-contact three-dimensional | (3D)
measurement techniques like those based on structured light
and passive stereo are examples of fields that have benefited
from all of these developments. In the case of passive
techniques (that use ambient light), only visible features with
discernable texture gradients like on intensity edges are
measured. Active systems and in particular, laser-based systems
are used to structure the environment in order to acquire dense
range maps from visible surfaces that are rather featureless to
the naked eye or a video camera. In order to take full advantage
973
and Spatial Information Sciences, Vol XXXV, Part B7. Istanbul 2004
of these vision systems, one must understand not only their
advantages but also their limitations. Baltsavias. 19992
compares photogrammetry and airborne laser scanning. This
section reviews the basic principles and best practices that
underline laser scanners and digital photogrammetry for 3D
vision systems in the case of close-range applications. We
emphasize laser scanning, as one specific scanner can't be used
for volumes of different sizes.
2.1 Laser scanners
Active sensors that use light waves for 3D measurements can be
divided into classes according to different characteristics. A
number of taxonomies exist in the literature (Nitzan, 1988;
Jühne et al., 1999). Here we summarize the main classes and
give the practical operating distance camera-to-object:
Triangulation: distance scanner-object about 0.1 em to 500 em
e Single spot (1D)
. Profile measurement (2D)
* — Area measurement (3D really 2.5D)
o Galvanometer-based laser scanning
o Laser probe combined with translation-
rotation motors, articulated arms and
coordinate measuring machines (CMM),
position trackers
o Multi-point and line projection based on
diffraction gratings
o Fringe and coded pattern projection
o Moiré effect
Time delay & light coherence
e Time of flight: 100 cm to several km
o Single point and mirror-based scanning
e Pulsed lasers
e AM or FM modulation
o Full field using micro-channel plates or
custom build silicon chips (pulsed or AM).
* Interferometric and Holographic: wide distance range
EA Laser
= source
Optical Laser
y Center spot
AZ sensor
Figure 1. Laser-based optical triangulation (single spot).
2.1.1 Triangulation
Triangles are the basis of many measurement techniques, from
basic geodesic measurements performed in ancient Greece to
16" century theodolite-based surveys and now modern laser-
based (or projector-based) 3D cameras. The basic geometrical
principle of optical triangulation is shown in Figure 1. To
acquire a full 3D image, one of the scanning techniques listed
above can be used. The collection of the scattered laser light
from the surface is done from a vantage point distinct from the
projected light beam. This light is focused onto a linear position
sensitive detector (herein called laser spot sensor) Knowing
