SEMANTIC PHOTOGRAMMETRY – BOOSTING IMAGE-BASED 3D RECONSTRUCTION WITH SEMANTIC LABELING

Corn 3d Reconstruction with Photogrammetry

Corn is a common crop which is often studied in the applications of remote sensing and precision agriculture. In both cases, it is important to know the geometrical structure of the corn, for example, the diameter and height of stem, the leaf areas and leaf directions. It is convenient to measure these geometrical structural data on a 3D corn model. In order to generate such a corn 3D model, an...

Semantic 3D Reconstruction with Finite Element Bases

We propose a novel framework for the discretisation of multi-label problems on arbitrary, continuous domains. Our work bridges the gap between general FEM discretisations, and labeling problems that arise in a variety of computer vision tasks, including for instance those derived from the generalised Potts model. Starting from the popular formulation of labeling as a convex relaxation by functi...

Semantic-Based Image Retrial in the VQ Compressed Domain using Image Annotation Statistical Models

Semantic 3D Reconstruction of Heads

i x i s = 1, x i s ≥ 0, x ij s ≥ 0 . • x i s ∈ [0, 1]: indicates whether label i is chosen at voxel s • y ij s = x ij s − x s ∈ [−1, 1]: presence of a surface and its direction • ρs: unary term, cost for label i at location s •φij s : convex smoothness term at voxel s for labels i and j • ek ∈ R: k-th canonical basis vector • T : alignment between prior and input data •α: normalization factor f...

Local Label Descriptor for Example Based Semantic Image Labeling

In this paper we introduce the concept of local label descriptor, which is a concatenation of label histograms for each cell in a patch. Local label descriptors alleviate the label patch misalignment issue in combining structured label predictions for semantic image labeling. Given an input image, we solve for a label map whose local label descriptors can be approximated as a sparse convex comb...