Effect of three-dimensional object type and density in simulated low-level flight.

1989 ◽  
Author(s):  
James A. Kleiss ◽  
David C. Hubbard ◽  
David G. Curry
Keyword(s):  
Three Dimensional ◽  
Object Type ◽  
Low Level ◽  
Level Flight ◽  
Dimensional Object

Effect of Three-Dimensional Object Type and Density in Simulated Low-Level Flight

1988 ◽  
Vol 32 (18) ◽  
pp. 1299-1303 ◽  
Author(s):  
James A. Kleiss ◽  
David G. Curry ◽  
David C. Hubbard
Keyword(s):  
Three Dimensional ◽  
Apparent Size ◽  
Abstract Objects ◽  
Processing Capacity ◽  
Object Type ◽  
Individual Object ◽  
Low Level ◽  
Three Dimensional Objects ◽  
Level Flight ◽  
Dimensional Object

Three-dimensional objects placed on simulated terrain surfaces are particularly effective as cues for altitude in simulated low-level flight. To conserve the limited edge processing capacity of computer image generators (CIGs), objects have typically been simple in shape and therefore fairly abstract in appearance. The present investigation sought to determine whether the apparent size of more detailed and familiar appearing objects (e.g., trees and bushes) serves as an additional cue for altitude in simulated low-level flight. Results showed no differences in performance between abstract objects and familiar objects. However, performance did improve with increases in object density, at least for some performance measures. These results suggest that CIG processing capacity may be most effectively utilized by increasing object density rather than individual object detail.

Low-level aspects of segmentation and recognition

1992 ◽  
Vol 337 (1281) ◽  
pp. 371-379 ◽  
Keyword(s):  
Three Dimensional ◽  
Contour Length ◽  
Two Dimensional ◽  
Linear Combinations ◽  
Low Level ◽  
Parallel Network ◽  
Three Dimensional Models ◽  
Dimensional Object ◽  
Candidate Object ◽  
Selection Of

This paper discusses two problems related to three-dimensional object recognition. The first is segmentation and the selection of a candidate object in the image, the second is the recognition of a three-dimensional object from different viewing positions. Regarding segmentation, it is shown how globally salient structures can be extracted from a contour image based on geometrical attributes, including smoothness and contour length. This computation is performed by a parallel network of locally connected neuron-like elements. With respect to the effect of viewing, it is shown how the problem can be overcome by using the linear combinations of a small number of two-dimensional object views. In both problems the emphasis is on methods that are relatively low level in nature. Segmentation is performed using a bottom -up process, driven by the geometry of image contours. Recognition is performed without using explicit three-dimensional models, but by the direct manipulation of two-dimensional images.

Reconstruction of Objects from their Projections Using Orthogonal Functions

1973 ◽  
Vol 31 ◽  
pp. 268-269
Author(s):  
Elrnar Zeitler
Keyword(s):  
Unit Area ◽  
Three Dimensional ◽  
One Dimension ◽  
Spatial Density ◽  
Dimensional Representation ◽  
Orthogonal Functions ◽  
Object A ◽  
Plane Normal ◽  
Dimensional Object ◽  
Spatial Density Distribution

Considering any finite three-dimensional object, a “projection” is here defined as a two-dimensional representation of the object's mass per unit area on a plane normal to a given projection axis, here taken as they-axis. Since the object can be seen as being built from parallel, thin slices, the relation between object structure and its projection can be reduced by one dimension. It is assumed that an electron microscope equipped with a tilting stage records the projectionWhere the object has a spatial density distribution p(r,ϕ) within a limiting radius taken to be unity, and the stage is tilted by an angle 9 with respect to the x-axis of the recording plane.

Urban network of China from the perspective of population mobility: Three-dimensional co-occurrence of nodes and links

2021 ◽  
pp. 0308518X2199781
Author(s):  
Xinyue Luo ◽  
Mingxing Chen
Keyword(s):  
Three Dimensional ◽  
Geographical Distance ◽  
Two Dimensional ◽  
Population Mobility ◽  
Urban Network ◽  
Urban Networks ◽  
Low Level ◽  
Medium Level ◽  
High Level ◽  
External Connections

The nodes and links in urban networks are usually presented in a two-dimensional(2D) view. The co-occurrence of nodes and links can also be realized from a three-dimensional(3D) perspective to make the characteristics of urban network more intuitively revealed. Our result shows that the external connections of high-level cities are mainly affected by the level of cities(nodes) and less affected by geographical distance, while medium-level cities are affected by the interaction of the level of cities(nodes) and geographical distance. The external connections of low-level cities are greatly restricted by geographical distance.

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