Open AccessJournal Article
Using genetic algorithms is computer vision: registering images to 3D surface model
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TL;DR: This paper focuses on the 2D-3D registration problem: given a 3D geometric model of an object, and optical images of the same object, the need to find the precise alignment of the 2d images to the 3D model.
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Abstract: This paper shows a successful application of genetic algorithms in computer vision. We aim at building photorealistic 3D models of real-world objects by adding textural information to the geometry. In this paper we focus on the 2D-3D registration problem: given a 3D geometric model of an object, and optical images of the same object, we need to find the precise alignment of the 2D images to the 3D model.
We generalise the photo-consistency approach of Clarkson et al. who assume calibrated cameras, thus only the pose of the object in the world needs to be estimated. Our method extends this approach to the case of uncalibrated cameras, when both intrinsic and extrinsic camera parameters are unknown. We formulate the problem as an optimisation and use a genetic algorithm to find a solution.
We use semi-synthetic data to study the effects of different parameter settings on the registration. Additionally, experimental results on real data are presented to demonstrate the efficiency of the method.
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Citations
Construction of lunar DEMs based on reflectance modelling
TL;DR: In this article, a variational surface reconstruction method was proposed to increase the lateral resolution of the DEM such that it reaches that of the underlying images, and an illumination-independent image registration scheme was developed.
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Atlas-based image segmentation: A Survey
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•Dissertation
Modélisation d'objets 3D par fusion silhouettes-stéréo à partir de séquences d'images en rotation non calibrées
Carlos Hernández Esteban
- 04 May 2004
TL;DR: Une nouvelle approche pour the modelisation d'objets 3D de haute qualite a partir de sequences d'images en rotation partiellement calibrees, yn ôl fournit une maniere robuste d'integrer les silhouettes dans l'evolution du modele deformable.
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Camera Self Calibration with Varying Parameters by an Unknown Three Dimensional Scene Using the Improved Genetic Algorithm
TL;DR: Compared with traditional optimization methods, the camera self-calibration by this approach can avoid being trapped in a local minimum, and converges quickly toward the optimal solution without initial estimate of the cameras parameters.
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•Proceedings Article
DEM construction and calibration of hyperspectral image data using pairs of radiance images
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TL;DR: This paper presents a framework for the reconstruction of digital elevation maps (DEM) from hyperspectral imagery and preexisting elevation data of lower lateral resolution, which consists of a combined photoclinometry and shape from shading scheme, which is extended towards photometric stereo using multiple images.
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