A study for scalable representation of 3D object models and its applications based on information sensitivity

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In this project, we propose a new method for 3D object model representation and its applications based on a concept of objective sensitivity to a 3D shape, which can deal with multi-view and multi-resolution range data, stereo images, texture images and videos. The objective sensitivity means how much information about the object can be obtained, when its 3D shape is presented in a certain level of detail. The work contains the following sub-goals : The first one is to integrate range data measured in different resolutions and from different view points by considering two certainties for each measured point, and then to generate a 3D shape model in a certain resolution level by using mesh adaptations like subdivision and decimation techniques. Some experimental results have proved that the goal has been achieved.The second goal is to propose a statistical texture analysis method that can extract some 3D scale factor from a natural image taken in an outdoor scene, where it is not so eas … More y to perform 3D measurement without using an expensive tool such as a laser range finder. The method is based on a hierarchical linear discriminant analysis that can classify some features calculated from higher-order local auto-correlation functions. It has been proved that the method is available for extracting 3D scale factor from texture images. We have also constructed an active stereo vision system that can control panning, tilting and zooming of the camera as an intelligent vision system of a robot. This system can gather some available information of a scene in the local system without any request from outside.The third goal is to develop a new cross-parameterization technique between 3D mesh models that can be used in various 3 dimensional Digital Geometry Processings (DGP). The cross-parameterization method proposed is based on a least-square mesh technique and a self-organizing deformable model(SDM) developed by the authors. This technique has enabled us to transfer texture and motion attributes of a 3D model to another one directly, or to generate intermediate models between two 3D mesh models. As a special application of the 3D morphing that presents these intermediate models temporally, we did several psychological experiments where subjects answer their results when they recognize what an intermediate shape presented is. These experiments have shown that their cognitive processes depend on the combination of the source and target object models.Finally, as other applications of the proposed method, we have developed a facial enhancement system based on the SDM, a 3D motion synthesis system based on a machine learning and a clustering algorithm, and a 3D video reconstruction system based on a factorization method. Less