Construction method of virtual scene generation-oriented video image material library

Abstract

The invention discloses a construction method of a virtual scene generation-oriented video image material library. The method includes the steps that first, an ontology concept and an expression of a video image material in the virtual scene generation field are defined; then, ontology information is converted into a relational data base description from an OWL description, so that the video image material library is constructed; video image material semantics needed for generating a virtual scene is annotated in the three semantic levels of objects, actions and events by combining the constructed video image material library according to application requirements for generating the virtual scene, and the video image material semantics is written into a material annotation library; or the video image material in the video image material library is retrieved in the three semantic levels of objects, actions and events; through the method, the video image material needed for generating the virtual scene can be provided, the video image material library is effectively recognized and managed, and therefore data base support is provided for a virtual scene generation system based on the video image material.

Description

technical field [0001] The invention relates to the technical field of databases, in particular to a method for constructing a video image material library oriented to virtual scene generation. Background technique [0002] At present, virtual scenes are widely used in game entertainment, military training, film and television production, medicine and other fields. In the work of model building, at the same time, in order to achieve a realistic rendering effect, it is often necessary to manually construct a large number of scene details, which is expensive and has a long working cycle. Based on the above reasons, video image material has gradually become an important resource in the field of virtual scene generation. On the one hand, camera technology is widely used in various fields of human production activities. Compared with 3D models, video image data has abundant sources and the acquisition process is more convenient; on the other hand, video images have the advantage...

AI Technical Summary

Problems solved by technology

[0003] The amount of digital video image data is increasing massively, and there is a lot of redundancy in various application fields. For example, in the production of film and television and advertising programs, the length of the actual filmed material is often several times or even dozens of times the length of the final edited film. , so it is necessary to put the material into the library for unified and effective management; on the other hand, material search occupies a large proportion in the work of film and television image editing. In order to facilitate users to locate suitable material data, semantic information should be marked for the material. To this end, a complete knowledge expression method is needed to label and express the material, but the existing technology lacks a set of construction methods for the video image semantic material library oriented to virtual scene generation

Images