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Chapter 1
DOI: 10.4018/978-1-5225-5246-8.ch001
ABSTRACT
Over the past years, 3D reconstruction has proved to be a challenge. With augmented reality and robot-
ics attracting more attention, the demand for efcient 3D reconstruction algorithms has increased. 3D
reconstruction presents a problem in computer vision and as a result, much work has been dedicated to
solving it. Diferent design choices were made to consider diferent components of the process. Examples
of these diferences are how the scanning process is tackled, how the 3D reconstructed world is repre-
sented, among other aspects. Therefore, an evaluation of these algorithms is necessary. This chapter
focuses on the properties that facilitate the evaluation of 3D reconstruction algorithms and provides an
evaluation of the various algorithms.
INTRODUCTION
Three-dimensional reconstruction, the process of building 3D models out of multiple 2D scans represent-
ing different views of some objects, has presented a challenging problem that attracted much research
attention for decades in computer vision. The hardness of the 3D reconstruction problem arises from
the necessity of correlating the locations, alongside colors, of some features among different 2D scans
in order to decide their locations in the 3D world. Due to the variance of applications, scanners setup
alongside the algorithms in use varies as well. In other words, the nature of the application enforces the
scanners setup and the algorithm in use. For example, 3D reconstructing an animated real life objects
that we cannot control its motion pattern (an animal for example) demands the multiple 2D scans to be
taken at once to capture the same pose in all views (as having multiple scanners in use at once). On the
other hand, for 3D reconstruction of other objects, a turntable and a single 2D camera can be enough.
3D Reconstruction
Algorithms Survey
Mohamed Karam Gabr
German University in Cairo, Egypt
Rimon Elias
German University in Cairo, Egypt