Abstract: A method for determining the orientation of a physical object in space which determines the orientation of the object from the images captured by a set of cameras distributed around an image capture space. The method includes a set of steps which comprise: capturing multiple images of the physical object at the same time instant, machine learning modules determining the estimate of the orientation of the physical object for each of the cameras using the captured images, and a central processing unit determining the orientation of the physical object with respect to a global reference by combining the different estimated orientations.

Abstract: The present invention relates to a method and system for the optical and geometric calibration of a device configured for reconstructing the three-dimensional shape of an object. The object is reconstructed from a set of images thereof acquired by a plurality of cameras, where said plurality of cameras must necessarily be calibrated so that reconstruction is carried out without errors. In the context of the invention, calibration consists of obtaining the extrinsic parameters of said plurality of cameras; that is, the positions of their optical centers and the spatial orientations of their optical axes.

Abstract: The present invention relates to a method of determining the coherence between a physical object and a numerical model representative of the shape of a physical object, wherein a specific use of the method according to the invention is assessing and quantifying manufacturing defects. The method is characterized by a set of steps comprising: capturing multiple images of the physical object; processing the images to produce a second numerical model of the physical object; in a computer, aligning the first numerical model and the second numerical model to generate a third numerical model according to specific sub-steps, wherein the third numerical model comprises a plurality of points representative of the shape of the captured physical object. Compared with the first numerical model, the third numerical model allows determining a measurement of the coherence between the physical object captured by means of images and the first numerical model representative thereof.

Abstract: A method for determining the orientation of a physical object in space which determines the orientation of the object from the images captured by a set of cameras distributed around an image capture space. The method includes a set of steps which comprise: capturing multiple images of the physical object at the same time instant, machine learning modules determining the estimate of the orientation of the physical object for each of the cameras using the captured images, and a central processing unit determining the orientation of the physical object with respect to a global reference by combining the different estimated orientations.

Abstract: The present invention relates to a method and system for the optical and geometric calibration of a device configured for reconstructing the three-dimensional shape of an object. The object is reconstructed from a set of images thereof acquired by a plurality of cameras, where said plurality of cameras must necessarily be calibrated so that reconstruction is carried out without errors. In the context of the invention, calibration consists of obtaining the extrinsic parameters of said plurality of cameras; that is, the positions of their optical centers and the spatial orientations of their optical axes.

Abstract: The present invention relates to a method of determining the coherence between a physical object and a numerical model representative of the shape of a physical object, wherein a specific use of the method according to the invention is assessing and quantifying manufacturing defects. The method is characterized by a set of steps comprising: capturing multiple images of the physical object; processing the images to produce a second numerical model of the physical object; in a computer, aligning the first numerical model and the second numerical model to generate a third numerical model according to specific sub-steps, wherein the third numerical model comprises a plurality of points representative of the shape of the captured physical object. Compared with the first numerical model, the third numerical model allows determining a measurement of the coherence between the physical object captured by means of images and the first numerical model representative thereof.