Multiple view geometry in computer visiond
Multiple view geometry in computer visiond
Minimax Entropy Principle and Its Application to Texture Modeling
Neural Computation
A stochastic grammar of images
Foundations and Trends® in Computer Graphics and Vision
Random Projections of Smooth Manifolds
Foundations of Computational Mathematics
Automated 3D Segmentation and Analysis of Cotton Plants
DICTA '11 Proceedings of the 2011 International Conference on Digital Image Computing: Techniques and Applications
Hierarchical matching of non-rigid shapes
SSVM'11 Proceedings of the Third international conference on Scale Space and Variational Methods in Computer Vision
Classification of plant structures from uncalibrated image sequences
WACV '12 Proceedings of the 2012 IEEE Workshop on the Applications of Computer Vision
Detailed reconstruction of 3D plant root shape
ICCV '11 Proceedings of the 2011 International Conference on Computer Vision
A pointwise smooth surface stereo reconstruction algorithm without correspondences
Image and Vision Computing
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With the recent developments of computer vision and automated systems in medical imaging or agriculture, there has been, in the last years, the necessity to adopt methods able to analyze and reconstruct three dimensional network structures, such as blood vessels, plant architecture or root structures, given one or more two dimensional images of the observed scene. This paper reviews recent work on this problem. Each of the examples cited designs a new method, each of which is different from previous methods already proposed. In this paper we review some of the developed methods and, due to the evident heterogenity of the methods, we classify them according to whether they apply a model to two dimensional details in images, or methods which recover a three dimensional representation (point cloud, or mesh), and then fit a network structure model to this representation.