Equipment and method for modeling three-dimensional (3D) object

Abstract

The invention provides equipment and a method for modeling a three-dimensional (3D) object. By the equipment and the method, a depth image and a multi-view-angle color image can be fused, so that the 3D object is automatically modeled on the basis of a predefined 3D object template. The equipment comprises an image receiving unit, a 3D template providing unit and an object modeling unit, wherein the image receiving unit is used for receiving the shot color image and depth image; the color image comprises a positive color image and at least two lateral color images at other view angles; the depth image is a positive depth image; the 3D template providing unit is used for providing the 3D object template predefined for a specific type of object; the 3D object template has a shape feature and a texture feature; and the object modeling unit is used for deforming the 3D object template provided by the 3D template providing unit based on the color image and the depth image which are received by the image receiving unit, and performing texture synthesis on the color image and the deformed 3D object template to generate a 3D object model.

Description

Technical field [0001] The present invention relates to three-dimensional (3D) object modeling technology, in particular to an effective device and method capable of automatically performing 3D object modeling based on a predefined 3D object template. Background technique [0002] In the field of three-dimensional (3D) computer graphics, 3D object modeling refers to the process of generating an arithmetic representation of any three-dimensional object, and the result of this process is called a 3D object model. [0003] 3D object modeling has a wide range of applications in digital entertainment and other fields. For example, 3D object modeling is required in technologies such as virtual reality, augmented reality, 3D movies, 3D games, and human-computer interaction. At present, most 3D object modeling needs to be implemented manually by relevant professionals. This method is not only time-consuming, but also requires a lot of human participation. [0004] On the other hand, in the ...

AI Technical Summary

Problems solved by technology

However, the nonlinear optimization process has its own drawbacks, namely, it is not robust and requires very good initial values ​​to achieve good performance

In addition, the optimization process usually requires iterative operations, so the speed is very slow

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