Robust and long-range multi-person identification using multi-task learning

An electronic device comprising:

• at least one processing device configured to:
• obtain image frames capturing one or more people in at least one scene;
• identify features of the image frames;
• provide the identified features to a trained spatiotemporal transformer machine learning model, the trained spatiotemporal transformer machine learning model configured to generate a set of features for each of the one or more people, the set of features for each person comprising facial features of the person and pose features of the person over time;
• perform face identification using the facial features in each set of features to generate one or more first embeddings representing at least one face of at least one of the one or more people;
• perform gait identification using the pose features in each set of features to generate one or more second embeddings representing at least one gait of at least one of the one or more people;
• and
• identify at least one of the one or more people based on the first and second embeddings.

A non-transitory machine readable medium containing instructions that when executed cause at least one processor of an electronic device to:

• obtain image frames capturing one or more people in at least one scene;
• identify features of the image frames;
• provide the identified features to a trained spatiotemporal transformer machine learning model, the trained spatiotemporal transformer machine learning model configured to generate a set of features for each of the one or more people, the set of features for each person comprising facial features of the person and pose features of the person over time;
• perform face identification using the facial features in each set of features to generate one or more first embeddings representing at least one face of at least one of the one or more people;
• perform gait identification using the pose features in each set of features to generate one or more second embeddings representing at least one gait of at least one of the one or more people;
• and
• identify at least one of the one or more people based on the first and second embeddings.