What is a visual torso?

In the computer display, the visual hull is a three -dimensional (3D) shape of an object that is extrapolated from several two -dimensional (2D) images taken at different angles around the object that approaches. Surface data on the shape of the object is obtained by monitoring the outline of the object in the figure, basically creates a silhouette of the object without a specific internal texture or detail. The silhouette collection, all extracted from pictures taken at different angles, is assembled together in 3D space and the area between known outline points is interpolated to form a 3D object that has a general 3D outline of a real object, albeit perhaps without so much detail. The process used to create a visual hull, also known as shape-zilhouette (SFS), can be faster, less demanding on the processor and cheaper implement than some stereoscopic techniques to capture 3D movement or detect 3D objects. Some applications that use Visual Hull involves detecting obstacles to computer vision, capturing Pbending for medical or other analytical purposes and virtual scanning of 3D objects when the SFS is carried out in highly controlled conditions.

The process of shaping the visual torso of the object from the set of images includes the insulation of the object silhouette from the background in the images. The exact location and orientation of cameras used to get images is also important for this process. In each picture, the image of the image observation is made a direct path to the scene space and ending in the outline of the displayed object. This is done for every picture and for an area where each path that resembles cones in 3D environments, Cross gives a very rough, block -like volume that contains an object in the size of the scene. For some applications such as computer vision, this information is Enough to allow basic avoidance of obstacles.

silhouettes can be further improved, so smaller geometric details are translated into a visual hull. They canInclude holes into the object as it could occur if the visual trunk was constructed from the images of the human standing with their feet apart or outstretched arms. One attribute of the shape of an object that cannot be precisely captured by SFS techniques is the concave surface because it does not contribute to the silhouette.

SFS technique to create a visual torso of the object can be incredibly detailed and accurate if refined algorithms are used in conjunction with controlled conditions to create source images. These conditions may include a single, consistent light source, static and measurable background and cameras that are precisely calibrated. Due to these conditions, very accurate 3D object models can be built and movement can be carried out without the need for marks, tracks or special Beyond Cameras.