Interactive object selection

A computer-implemented method of applying a neural network teachable by obtaining a dataset of 3D point clouds, each 3D point cloud including at least one object, each 3D point cloud being equipped with a specification of one or more graphical user-interactions each representing a respective selection operation of a same object in the 3D point cloud, and teaching, based on the dataset, a neural network configured for segmenting an input 3D point cloud including an object, the segmenting being based on the input 3D point cloud and on a specification of one or more input graphical user-interactions each representing a respective selection operation of the object in the 3D point cloud, the method comprising:

• obtaining a 3D point cloud including an object;
• and
• one or more iterations of:
• performing a selection operation of the object by performing one or more graphical user-interactions, and
• by applying the neural network, segmenting the 3D point cloud based on the 3D point cloud and on a specification of the one or more graphical user-interactions,
• wherein the obtaining of the dataset of 3D point clouds further includes:
• obtaining the 3D point clouds and, for each 3D point cloud, information about location of said same object in the 3D point cloud, and
• for each 3D point cloud:
• determining the specification by simulating each graphical user-interaction of the one or more graphical user-interactions, and
• equipping the 3D point cloud with the specification of the one or more graphical user-interactions.

A device comprising:

• a processor;
• and
• a non-transitory data storage medium having recorded thereon a neural network and a computer program,
• wherein the non-transitory data storage medium includes instructions that when executed by the processor causes the processor to be configured to:
• obtain a 3D point cloud including an object, and
• in one or more iterations:
• perform a selection operation of the object by performing one or more graphical user-interactions, and
• by applying the neural network, segment the 3D point cloud based on the 3D point cloud and on a specification of the one or more graphical user-interactions, and/or
• wherein the non-transitory data storage medium includes instructions that when executed by the processor causes the processor to be configured to:
• teach by machine-learning the neural network by the processor being further configured to:
• obtain a dataset of 3D point clouds, each 3D point cloud including at least one object, each 3D point cloud being equipped with a specification of one or more graphical user-interactions each representing a respective selection operation of a same object in the 3D point cloud, and
• teach, based on the dataset, a neural network configured for segmenting an input 3D point cloud including an object, the segmenting being based on the input 3D point cloud and on a specification of one or more input graphical user-interactions each representing a respective selection operation of the object in the 3D point cloud,
• wherein in the machine-learning, the processor is further configured to obtain the dataset of 3D point clouds by being configured to
• obtain the 3D point clouds and, for each 3D point cloud, information about location of said same object in the 3D point cloud;
• and
• for each 3D point cloud:
• determine the specification by simulating each graphical user-interaction of the one or more graphical user-interactions, and
• equip the 3D point cloud with the specification of the one or more graphical user-interactions.