This tutorial introduces a SciPy+OpenCV environment and shows how it can address different steps on computer vision research, from initial data exploration to parallel computing implementations.
A stereo approach for 3D plant modelling is presented. Using only a set of photographies, the method produces a dense 3D point cloud sampling the plant surface. Clustering automatically segments the plant structure in meaningful parts, which are classified in elements of interest as leaves and internodes. Measurements can be computed for each element, as area or surface normals.
This paper shows as the state of the art in structure from motion and multiple view stereo is able to produce accurate 3D models for specimens presenting sparse canopies. Three-dimensional triangular meshes are computed from a set of non-calibrated images, modeling a basil and an Ixora specimens and accurately representing their leaves and branches.
[pt-BR] Este trabalho apresenta algumas alternativas para digitalização de plantas, encontradas na literatura recente, que empregam diferentes técnicas de imageamento para obter, de forma automática ou semiautomática, modelos tridimensionais de plantas. Também são apresentadas técnicas de construção de modelos 3D utilizadas em outros domínios que podem ser a base para novos avanços em digitalização de plantas.
Our method combines a simple geometric model of the scene composed of planes (virtual environment), augmented with visual information from the cameras and pre-computed tracking information of moving targets to generate novel perspective corrected 3D views of the virtual camera and moving objects.
This paper proposes a method to locate and track people by combining evidence from multiple cameras using the homography constraint.
XXI Brazilian Symposium on Computer Graphics and Image Processing, 2008. SIBGRAPI ’08 Thiago T. Santos and Carlos H. Morimoto This…