Abstract: An electronic device: obtains a first set of subjects associated with a first pose of the device; determines likelihood estimate values for each of the first set of subjects based on user context and the first pose; determines whether at least one likelihood estimate value for at least one respective subject in the first set of subjects exceeds a confidence threshold; and generates recommended content or actions associated with the at least one respective subject using at least one classifier associated with the at least one respective subject and the user context in response to determining that the at least one likelihood estimate value exceeds the confidence threshold.

Abstract: An electronic device: obtains pass-through image data characterizing a field of view captured by an image sensor; determines whether a recognized subject in the pass-through image data satisfies a confidence score threshold associated with a user-specific recommendation profile; generates one or more computer-generated reality (CGR) content items associated with the recognized subject in response to determining that the recognized subject in the pass-through image data satisfies the confidence score threshold; and composites the pass-through image data with the one or more CGR content items, where the one or more CGR content items are proximate to the recognized subject in the field of view.