Moment Invariants for 3D Flow Fields
نویسندگان
چکیده
Moment invariants are popular descriptors for real valued functions. Their independence from certain transformations makes them a powerful tool for the recognition of patterns and shapes. It has recently been demonstrated that the basic ideas can also be transferred to vector valued functions. Vector moment invariants can be used to define and search for interesting flow structures. A generalization to three-dimensional vector valued functions so far has not been investigated at all. In this paper, we approach that problem. We introduce a definition of moments for three-dimensional vector fields and present how flow field invariants can be constructed from the normalization of the first order vector moment tensor.
منابع مشابه
Customized TRS invariants for 2D vector fields via moment normalization
The behavior of vector fields under translation, rotation and scaling differs withrespect to the underlying application. Moment invariants that are customized tothe specific problem can be constructed by means of normalization.In this paper, we calculate general TRS (translation, rotation, and scaling) mo-ment invariants for two-dimensional vector fields. As an example, we s...
متن کامل3D Polar-Radius Invariant Moments and Structure Moment Invariants
A novel moment, called 3D polar-radius-invariant-moment, is proposed for the 3D object recognition and classification. Some properties of these new moments including the invariance on translation, scale and rotation transforms are studied and proved. Then structure moment invariants are given to distinguish complicated similar shapes. Examples are presented to illustrate the performance and inv...
متن کاملTensor Method for Constructing 3D Moment Invariants
A generalization from 2D to 3D of the tensor method for derivation of both affine invariants and rotation, translation and scaling (TRS) invariants is described. The method for generation of the 3D TRS invariants of higher orders is automated and experimentally tested.
متن کامل3D Object Recognition Using Multiple Views, Affine Moment Invariants and Multilayered Perceptron Network
This paper addresses a performance analysis of affine moment invariants for 3D object recognition. Affine moment invariants are commonly used as shape feature for 2D object or pattern recognition. The current study proved that with some adaptation to multiple views technique, affine moments are sufficient to model 3D objects. In addition, the simplicity of moments calculation reduces the proces...
متن کاملSemantic Segmentation of Outdoor Areas Using 3D Moment Invariants and Contextual Cues
In this paper, we propose an approach for the semantic segmentation of a 3D point cloud using local 3D moment invariants and the integration of contextual information. Specifically, we focus on the task of analyzing forestal and urban areas which were recorded by terrestrial LiDAR scanners. We demonstrate how 3D moment invariants can be leveraged as local features and that they are on a par wit...
متن کامل