Method for matching and retrieving three-dimensional building models based on shape recognition

Abstract

The invention relates to a method for matching and retrieving three-dimensional building models based on shape recognition. At present, relatively mature information retrieving technologies are still limited to the aspect of text retrievals. Retrievals of images, three-dimensional models and the like are usually retrievals of relevant text information, which makes retrievals of such data and models low in accuracy. In the method, both self upper direction characteristics of a three-dimension building model and a principal direction on a horizontal plane are used, recognition theories are combined with classic LightField description operators by a model normalization method, and Horizontal LightField description operators are extracted from a series of model images corresponding to a simplified field by simplifying and rendering a light field of a standardized building model, wherein the Horizontal LightField description operators only require rotary matching in horizontal direction. Matching and retrieving of the three-dimensional building model is realized by utilizing shape qualitative description operators and shape quantitative description operators. Compared with previous methods, the method of the invention can better consider human recognition of space objects, and can give consideration to both accuracy and high efficiency of coupling. The invention provides a new method for building a three-dimensional digital city system in a rapid, cheap and automatic way.

Description

1. Technical field [0001] The invention relates to a method for matching and retrieving three-dimensional architectural models based on shape cognition, and belongs to the technical field of spatial information. 2. Background technology [0002] 3D digital city has important applications in military, city navigation, tourism, etc. As an important embodiment of city characteristics, architectural model is an important part of city entity. The current urban architectural models are usually: 1) obtained through field data collection, and then modeling and rendering. If there are many models involved, it will be time-consuming, labor-intensive and expensive; 2) Obtained from aerial photographs or high-resolution images, However, it is difficult to build high-resolution and realistic models with the modeling methods based on aerial photographs. Although Google Street-View, Microsoft Live Street-Side and 2D panorama based on fixed viewpoints can make up for this deficiency, many ...

AI Technical Summary

Problems solved by technology

The current search engine technology is still limited to text retrieval. The search for images, 3D models, etc. is usually to retrieve relevant text information, so the accuracy of searching for such data and models is very low.

Although relevant scholars have proposed different algorithms for 3D model search, the accuracy of urban 3D model search and matching still needs to be improved urgently.

Images