Abstract: A system is provided that stores a neural network model trained on a training dataset which indicates an association between first graphic information associated with one or more first objects and corresponding first plurality of depth images. The system receives second graphic information that corresponds to the one or more first objects. The system further applies the trained neural network model received on the second graphic information. The system predicts a first depth image from the first plurality of depth images based on the application of the trained neural network model on the received second graphic information. The system extracts first depth information from the predicted first depth image. The first depth information corresponds to the one or more first objects indicated by the second graphic information.

Abstract: A system for generation of training dataset is provided. The system controls a depth sensor to capture, from a first viewpoint, a first image a first depth value associated with the first object. The system receives tracking information from a handheld device associated with the depth sensor, based on a movement of the handheld device and the depth sensor in a 3D space. The system generates graphic information corresponding to the first object based on the received tracking information. The graphic information includes the first object from a second viewpoint. The system calculates a second depth value associated with the first object, based on the graphic information. The system generates, for a neural network model, a training dataset which includes a first combination of the first image and the first depth value, and a second combination of second images corresponding to the graphic information and the second depth value.

Abstract: A system for generation of training dataset is provided. The system controls a depth sensor to capture, from a first viewpoint, a first image a first depth value associated with the first object. The system receives tracking information from a handheld device associated with the depth sensor, based on a movement of the handheld device and the depth sensor in a 3D space. The system generates graphic information corresponding to the first object based on the received tracking information. The graphic information includes the first object from a second viewpoint. The system calculates a second depth value associated with the first object, based on the graphic information. The system generates, for a neural network model, a training dataset which includes a first combination of the first image and the first depth value, and a second combination of second images corresponding to the graphic information and the second depth value.

Abstract: A system is provided that stores a neural network model trained on a training dataset which indicates an association between first graphic information associated with one or more first objects and corresponding first plurality of depth images. The system receives second graphic information that corresponds to the one or more first objects. The system further applies the trained neural network model received on the second graphic information. The system predicts a first depth image from the first plurality of depth images based on the application of the trained neural network model on the received second graphic information. The system extracts first depth information from the predicted first depth image. The first depth information corresponds to the one or more first objects indicated by the second graphic information.

Abstract: A computer-implemented system and method for enabling content information ingestion and processing in a content browsing and recommendation system are disclosed. The system and method in an example embodiment includes: gathering available content information related to particular items of content from a plurality of content sources via a data network; normalizing the gathered content information by using an ingestion engine; processing the content information, using a data processor, to associate particular items of content information with content catalogs; and storing the processed content information into a database with information identifying associated content catalogs.

Abstract: A computer-implemented system and method for enabling content integration in a content browsing and recommendation system are disclosed. The system and method in an example embodiment includes: gathering available content information related to particular items of content from a plurality of content sources via a data network; processing the content information, using a data processor, to provide a searchable database of processed content information; providing a service, accessible via the data network, to enable a user platform to request a search of the processed content information and identify a selected content item; and directing at least one content source to provide the selected content item directly to the user platform.

Abstract: A computer-implemented system and method for enabling content recommendation in a content browsing and recommendation system are disclosed.

Abstract: A computer-implemented system and method for enabling data delivery in a content browsing and recommendation system are disclosed. The system and method in an example embodiment include: gathering available content information related to particular items of content from a plurality of content sources via a data network; processing the content information, using a data processor, to associate particular items of content information with content catalogs; storing the processed content information into a database with information identifying associated content catalogs; and providing a service, accessible via the data network, to enable a user platform to search the processed content information in the database based on a content catalog identifier.