"Seeing" Objects in Spatial Datasets
نویسندگان
چکیده
Regularities exist in datasets describing spatially distributed physical phenomena. Human experts often understand and verbalize the regularities as abstract spatial objects evolving coherently and interacting with each other in the domain space. We describe a novel computational approach for identifying and extracting these abstract spatial objects through the construction of a hierarchy of spatial relations. We demonstrate the approach with an application to nding troughs in weather data sets.
منابع مشابه
Matching of Polygon Objects by Optimizing Geometric Criteria
Despite the semantic criteria, geometric criteria have different performances on polygon feature matching in different vector datasets. By using these criteria for measuring the similarity of two polygons in all matchings, the same results would not have been obtained. To achieve the best matching results, the determination of optimal geometric criteria for each dataset is considered necessary....
متن کاملSelection of Spatial Reference Directions Prior to Seeing Objects
Three experiments examined the temporal characteristics in selection of a spatial reference direction. Participants learned a layout of objects presented sequentially in a random order. An array of disks with a symmetric axis different from participants’ learning viewpoint was presented before, during, or after learning objects’ locations. The results showed that the symmetric axis determined s...
متن کاملDeblurring and Sparse Unmixing of Hyperspectral Images Using Multiple Point Spread Functions
This paper is concerned with deblurring and spectral analysis of ground-based astronomical images of space objects. A numerical approach is provided for deblurring and sparse unmixing of ground-based hyperspectral images (HSI) of objects taken through atmospheric turbulence. Hyperspectral imaging systems capture a 3D datacube (tensor) containing: 2D spatial information, and 1D spectral informat...
متن کاملA Clustering Approach by SSPCO Optimization Algorithm Based on Chaotic Initial Population
Assigning a set of objects to groups such that objects in one group or cluster are more similar to each other than the other clusters’ objects is the main task of clustering analysis. SSPCO optimization algorithm is anew optimization algorithm that is inspired by the behavior of a type of bird called see-see partridge. One of the things that smart algorithms are applied to solve is the problem ...
متن کاملRelation-based aggregation: finding objects in large spatial datasets
Regularities exist in datasets describing spatially distributed physical phenomena. Human experts often understand and verbalize the regularities as abstract spatial objects evolving coherently and interacting with each other in the domain space. We describe a novel computational approach for identifying and extracting these abstract spatial objects through the construction of ahierarchy of spa...
متن کامل