A method comprising: at a device including one or more processors and a non-transitory memory: obtaining image data characterizing a field of view captured by an image sensor; determining whether a recognized subject in the image data satisfies a confidence score threshold associated with a user-specific recommendation profile indicating a user's interest in the recognized subject; generating one or more computer-generated reality, CGR, content items associated with the recognized subject in response to determining that the recognized subject in the image data satisfies the confidence score threshold; and compositing the image data with the one or more CGR content items, wherein the one or more CGR content items are displayed proximate to the recognized subject in the field of view; wherein the recognized subject in the image data is recognized by: determining a region in the field of view where the user is gazing at; obtaining a subset of the image data corresponding to the region; and recognizing the recognized subject based on the subset of the image data and a classifier; and characterized in that the method further comprises: assigning weights to classifiers based on the gaze, wherein each of the classifiers is associated with a respective subject in the region; adjusting the weights to the classifiers based on updates of the gaze; and selecting the classifier from the classifiers with a highest weight as the classifier to be used for recognizing the recognized subject. obtaining image data characterizing a field of view captured by an image sensor; determining whether a recognized subject in the image data satisfies a confidence score threshold associated with a user-specific recommendation profile indicating a user's interest in the recognized subject; generating one or more computer-generated reality, CGR, content items associated with the recognized subject in response to determining that the recognized subject in the image data satisfies the confidence score threshold; and compositing the image data with the one or more CGR content items, wherein the one or more CGR content items are displayed proximate to the recognized subject in the field of view; wherein the recognized subject in the image data is recognized by: determining a region in the field of view where the user is gazing at; obtaining a subset of the image data corresponding to the region; and recognizing the recognized subject based on the subset of the image data and a classifier; and characterized in that determining a region in the field of view where the user is gazing at; obtaining a subset of the image data corresponding to the region; and recognizing the recognized subject based on the subset of the image data and a classifier; and characterized in that the method further comprises: assigning weights to classifiers based on the gaze, wherein each of the classifiers is associated with a respective subject in the region; adjusting the weights to the classifiers based on updates of the gaze; and selecting the classifier from the classifiers with a highest weight as the classifier to be used for recognizing the recognized subject. assigning weights to classifiers based on the gaze, wherein each of the classifiers is associated with a respective subject in the region; adjusting the weights to the classifiers based on updates of the gaze; and selecting the classifier from the classifiers with a highest weight as the classifier to be used for recognizing the recognized subject. <EOS>