Training and implementing a four-dimensional data object recommendation model

A method, comprising:

• receiving an input four-dimensional (4D) data object including a time-series three-dimensional (3D) model of an individual and annotations associated with the individual, the time-series 3D model including media content captured by a multi-camera system and combined into 3D models showing movement of the individual over a duration of time;
• applying a 4D recommendation model to the input 4D data object to generate a recommendation output for the input 4D data object, the 4D recommendation model being configured to:
• identify features of a given 4D data object;
• compare the identified features to features of a knowledge base of 4D data objects to determine a subset of 4D data objects from the knowledge base having a threshold similarity to the given 4D data object;
• compare the given 4D data object to the subset of 4D data objects from the knowledge base to determine that one or more features are missing from the given 4D data object;
• and
• generate an output including a recommendation associated with the subset of 4D data objects and based on determining that the one or more features are missing from the given 4D data object, the recommendation including a gesture to perform by a given individual such that capturing additional media content while the given individual performs the gesture would capture the one or more features that are missing within the given 4D data object;
• and
• causing a presentation of the recommendation output to be displayed via a graphical user interface of a client device, prompting the individual to perform the gesture while the multi-camera system captures additional media content to update the 4D data object.

A system, comprising:

• at least one processor;
• memory in electronic communication with the at least one processor;
• and
• instructions stored in the memory, the instructions being executable by the at least one processor to:
• receiving a plurality of four-dimensional (4D) data objects, the plurality of 4D data objects including time-series three-dimensional (3D) models of individuals and annotations associated with the time-series 3D models, each time-series 3D model from the plurality of 4D objects including media content captured by a multi-camera system and combined into 3D models showing movement of an individual over a duration of time;
• generating a knowledge base of the plurality of 4D data objects, the knowledge base including an accessible storage of the plurality of 4D data objects;
• and
• training a 4D recommendation model to:
• identify features of a given 4D data object;
• compare the identified features to features of the knowledge base of the plurality of 4D data objects to determine a subset of 4D data objects from the knowledge base having a threshold similarity to the given 4D data object;
• compare the given 4D data object to the subset of 4D data objects from the knowledge base to determine that one or more features are missing from the given 4D data object;
• and
• generate an output including a recommendation associated with the subset of 4D data objects and based on determining that the one or more features are missing from the given 4D data object, the recommendation including a gesture to perform by a given individual such that capturing additional media content while the given individual performs the gesture would capture the one or more features that are missing from the given 4D data object.