# A High-Resolution Texture Mapping Technique for 3D Textured Model
## 1 Introduction  
Two-dimensional (2D) images are commonly used for product presentations in e-commerce because they can reveal the object's texture and are easy to process. However, as 2D images can display only limited views of an object, it may be possible to capture hundreds of 2D images and orient an image at any viewing angle via a web viewer [1]. However, storing and displaying so many images while maintaining high image quality would have huge memory requirements. In addition, the actual three-dimensional (3D) shape and dimensions of an object cannot be obtained in this representation. 3D image-modeling technology is a technique for reconstructing the 3D model of an object by using multiple 2D images while maintaining its texture on the model (called 3D textured model hereafter). If its texture quality can be comparable to that of 2D images, this technology could be used to replace 2D images for product presentations, because a 3D textured model requires less memory and can freely be oriented in 3D space. Product presentation usually requires a dedicated photography device to catch high-quality object images with known position and orientation in 3D space. The object images can be obtained using a single-camera device that applies a digital single-lens reflex (DSLR) camera to capture an object placed on a turntable, or a multi-camera device that applies several DSLR cameras mounted on an arm to capture an object placed on a turntable from different angles. These devices can position thecamera precisely such that the camera information can be calibrated. The object on the turntable can also be oriented to capture object images in different views. These devices also provide a controlled environment, for example, single background color and adjustable lighting, such that the object images and the background color can easily be separated. As these devices are already used in the field of product presentation, we use them as the image source of the 3D-image modeling technology. 3D image-modeling technology primarily involves the generation of two kinds of information, the 3D model of an object and its texture map. The former employs triangular meshes to describe the object's surface geometry, and the latter describes its color information. There is a mapping between the 3D model and the texture map such that when the model is displayed in 3D space, accurate object texture can be displayed accordingly. Approaches to generating 3D models from multiple images can be classified into two groups: shape-from-silhouette (SFS) and shape-from-photoconsistency (SFP). The SFP approach has received extensive attention because it can simultaneously yield a 3D geometric model of an object and its texture map. The main idea of this method is to generate photo-consistent models that can reduce some measure of the discrepancy between different image projections of their surface vertices [2; 3; 4]. The main advantage of the SFP approach is that it can generate fine surface details by using photometric and geometric information. However, the reliability of the SFP approach remains a problem because the texture quality can easily be affected by environmental factors such as noise in the colors, inaccuracies in camera calibration, non-Lambertian surfaces, and homogeneous object color. However, the SFS approach is a common method used to estimate an object's shape from images of its silhouettes [5; 6; 7]. This method is essentially based on a visual hull concept in which the object's shape is constructed by the intersection of multiple sets of polygons from the silhouettes of multiple 2D images. With a sufficient number of images from different views, this method can yield an approximate model to describe the outline shape of an object. However, this model is not yet suitable for visualization due to the following two reasons.