Range searching and point location among fat objects

Author(s):  
Mark H. Overmars ◽  
A. Frank van der Stappen
1996 ◽  
Vol 21 (3) ◽  
pp. 629-656 ◽  
Author(s):  
Mark H. Overmars ◽  
Frank A. van der Stappen

Algorithmica ◽  
2018 ◽  
Vol 81 (5) ◽  
pp. 1921-1937
Author(s):  
Xiaocheng Hu ◽  
Cheng Sheng ◽  
Yufei Tao
Keyword(s):  

2020 ◽  
Vol 15 ◽  
pp. 155892502097832
Author(s):  
Jiaqin Zhang ◽  
Jingan Wang ◽  
Le Xing ◽  
Hui’e Liang

As the precious cultural heritage of the Chinese nation, traditional costumes are in urgent need of scientific research and protection. In particular, there are scanty studies on costume silhouettes, due to the reasons of the need for cultural relic protection, and the strong subjectivity of manual measurement, which limit the accuracy of quantitative research. This paper presents an automatic measurement method for traditional Chinese costume dimensions based on fuzzy C-means clustering and silhouette feature point location. The method is consisted of six steps: (1) costume image acquisition; (2) costume image preprocessing; (3) color space transformation; (4) object clustering segmentation; (5) costume silhouette feature point location; and (6) costume measurement. First, the relative total variation model was used to obtain the environmental robustness and costume color adaptability. Second, the FCM clustering algorithm was used to implement image segmentation to extract the outer silhouette of the costume. Finally, automatic measurement of costume silhouette was achieved by locating its feature points. The experimental results demonstrated that the proposed method could effectively segment the outer silhouette of a costume image and locate the feature points of the silhouette. The measurement accuracy could meet the requirements of industrial application, thus providing the dual value of costume culture research and industrial application.


2012 ◽  
Vol 34 (3) ◽  
pp. 319 ◽  
Author(s):  
Anke S. K. Frank ◽  
Chris R. Dickman ◽  
Glenda M. Wardle

The activities of livestock in arid environments typically centre on watering points, with grazing impacts often predicted to decrease uniformly, as radial piospheres, with distance from water. In patchy desert environments, however, the spatial distribution of grazing impacts is more difficult to predict. In this study sightings and dung transects are used to identify preferred cattle habitats in the heterogeneous dune system of the Simpson Desert, central Australia. The importance of watering points as foci for cattle activity was confirmed and it was shown that patchily distributed gidgee woodland, which comprises only 16% of the desert environment, is the most heavily used habitat for cattle away from water and provides critical forage and shade resources. By contrast, dune swales and sides, which are dominated by shade- and forage-deficient spinifex grassland and comprise >70% of the available habitat, were less utilised. These results suggest that habitat use by cattle is influenced jointly by water point location and by the dispersion of woodland patches in a resource-poor matrix. The findings were used to build a modified conceptual model of cattle habitat use which was compared with an original piosphere model, and the consequences for wildlife in environments where the model applies are discussed.


2004 ◽  
Vol 12 (4) ◽  
pp. 354-374 ◽  
Author(s):  
Bruce Western ◽  
Meredith Kleykamp

Political relationships often vary over time, but standard models ignore temporal variation in regression relationships. We describe a Bayesian model that treats the change point in a time series as a parameter to be estimated. In this model, inference for the regression coefficients reflects prior uncertainty about the location of the change point. Inferences about regression coefficients, unconditional on the change-point location, can be obtained by simulation methods. The model is illustrated in an analysis of real wage growth in 18 OECD countries from 1965–1992.


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