Abstract: Methods of and systems for characterization of a 3D point cloud are disclosed. The method comprises accessing a 3D point cloud, the 3D point cloud being a set of data points representative of the object, determining, based on the 3D point cloud, a 3D reconstructed object, determining, based on the 3D reconstructed object, a digital framework of the 3D point cloud, the digital framework being a ramified 3D tree structure, the digital framework being representative of a base structure of the object, morphing a 3D reference model of the object onto the 3D reconstructed object, the morphing being based on the digital framework; and determining, based on the morphed 3D reference model and the 3D reconstructed object, characteristics of the object.

Abstract: The disclosed systems, components, methods, and processing steps are directed to determining user-item fit characteristics of an item for a user body part by accessing a three-dimensional (3D) reconstructed model of the user body part, accessing information about one or more 3D reference models of the item, the information for each 3D reference model including respective dimensional measurement, spatial, and geometrical attributes, performing a 3D matching process based on the 3D reconstructed model and the accessed information of the one or more 3D reference models to determine a best-fitting 3D reference model from the one or more 3D reference models, integrating the best-fitting 3D reference model with the 3D reconstructed model to provide a 3D best fit representation and displaying the 3D best fit representation along with visual indications of user-item fit characteristics.

Abstract: A 3D objects training dataset is augmented by accessing a 3D point cloud representation of an object and by applying an augmentation routine on the point cloud to generate an augmented point cloud. The augmentation routine comprises randomly selecting an execution order of at least one of (i) adding a noise to the point cloud, (ii) applying a geometric transformation on the point cloud and (iii) applying a degradation on the point cloud. The randomly selected execution order of these operations on the point cloud is applied, and the augmented point cloud is added to the objects training dataset. A machine learning algorithm (MLA) is trained by inputting the 3D point cloud representation to generate an output, comparing the output with an expected label associated with the point cloud representation to determine a measure of error on the output, and iteratively adjusting various weights associated with nodes of the MLA.

Abstract: The present disclosure proposes a computer implemented of object recognition of an object to be identified using a method for reconstruction of a 3D point cloud. The method comprises the steps of acquiring, by a mobile device, a plurality of pictures of said object, sending the acquired pictures to a cloud server, reconstructing, by the cloud server, a 3D points cloud reconstruction of the object, performing a 3D match search in a 3D database using the 3D points cloud reconstruction, to identify the object, the 3D match search comprising a comparison of the reconstructed 3D points cloud of the object with 3D points clouds of known objects stored in the 3D database.

Abstract: The present disclosure proposes a computer implemented of object recognition of an object to be identified using a method for reconstruction of a 3D point cloud. The method comprises the steps of acquiring, by a mobile device, a plurality of pictures of said object, sending the acquired pictures to a cloud server, reconstructing, by the cloud server, a 3D points cloud reconstruction of the object, performing a 3D match search in a 3D database using the 3D points cloud reconstruction, to identify the object, the 3D match search comprising a comparison of the reconstructed 3D points cloud of the object with 3D points clouds of known objects stored in the 3D database.

Abstract: A computer implemented method for reconstructing a 3D point cloud of an object, and a method of object recognition of an object to be identified using the method for reconstruction of a 3D point cloud.