## 2 Materials and Methods
### Shape from Stereo SfS  
Stereovision, also known as binocular vision, is a technique of perceiving the environment through the use of an optical system that produces dual imaging from two different perspectives. The concept of stereovision was inspired by the natural world, where humans and animals utilize a pair of eyes to navigate and perceive their surroundings. This faculty of spatial perception has been preserved through evolution in most animal species. This observation underscores the efficacy of stereovision. The implementation of stereovision has expanded significantly in recent years, with applications ranging from robotics and autonomous systems to object digitization and distance measurement, virtual and augmented reality, and medicine. The process of stereovision digitization (SfS) involves the utilization of the fundamental principle of space perception by an optical system equipped with a pair of sensors, employing distance measurements between the optical system and objects in space for the purpose of digitization. The objective of the SfS-based digitization process is to generate a depth image, point cloud, or a surface model that accurately represents the actual surface of a physical object within a scene, given a real-world coordinate system and the coordinate system of the digitizing device. The SfS-based digitization process employs a dual-sensing optical system situated in space, with two optical sensors capturing the space from different perspectives. The SfS employs the parallax effect, which manifests as a perceptual shift in the perceived position of an object when observed from two distinct positions due to a change in perspective at varying angles or distances. SfS digitizing is a particular digitizing technique that utilizes triangulation and photogrammetry as its fundamental mathematical model. Photogrammetry can be defined as a three-dimensional measurement technique that uses central projection imaging as its underlying mathematical model. Photogrammetry involves measurement methods based on image datasets and their interpretation to obtain the surface, shape, and location of a physical object based on one or more photographs of that object. To employ photogrammetry techniques for the digitization of objects, it is imperative to ascertain the precise location of cameras within the scene to facilitate the requisite calculations. The reconstruction of physical models based on image-based calculations entails the generation of point features on the object, with these features being derived from the object's shape, brightness, and color distribution as depicted in the images. At the initiation of the physical object reconstruction process employing photogrammetry, it is imperative to establish a methodology for interpreting and measuring the images, thereby facilitating the creation of these point features. To this end, the employment of measuring and sensing devices characterized by the requisite geometric and optical quality characteristics is required [21]. The SfS digitization process utilizes dual-imaging, which involves the use of a pair of optical sensors to capture binocular stereo images of the scene. This technique is analogous to the manner in which humans perceive visual information, enabling the acquisition of three-dimensional data concerning the surface characteristics of an object. The process employs a computation designed to obtain an exact match of a particular surface point on both images. However, the utilization of passive stereovision, devoid of the illumination provided by a specific light pattern, demonstrates comparatively diminished accuracy and relies extensively on block registration of regions exhibiting similar disparity across the image. Notable examples include Stereo Block Matching (abbreviated BM) and Stereo Semi-Global Block Matching (abbreviated SGBM). In this context, the registration of common visual features for disparity computation can also be considered problematic.