An image processing system, comprising: at least one camera for capturing images of a surrounding environment; a display, at least one processor, and memory containing software; wherein the software directs the at least one processor to: obtain data (103, 202) comprising a sequence of images captured by the at least one camera; detect a face for at least one person within a plurality of images in the sequence of images; detect at least one emotional cue in the face based upon the plurality of images using a classifier; identify at least one emotion based on the emotional cue; and display at least one emotion indicator label in real time to provide therapeutic feedback; wherein the classifier is trained using a training data set of statistically representative emotional cue data, and characterised in that the software directs the at least one processor to further carry out a calibration of the classifier for a target individual by supplementing the training data set with at least one image of the target individual and a corresponding user provided label of the emotional cue of the target individual and retraining the classifier for the target individual using the emotional cue and the corresponding label of the emotional cue of the target individual. at least one camera for capturing images of a surrounding environment; a display, at least one processor, and memory containing software; wherein the software directs the at least one processor to: obtain data (103, 202) comprising a sequence of images captured by the at least one camera; detect a face for at least one person within a plurality of images in the sequence of images; detect at least one emotional cue in the face based upon the plurality of images using a classifier; identify at least one emotion based on the emotional cue; and display at least one emotion indicator label in real time to provide therapeutic feedback; wherein the classifier is trained using a training data set of statistically representative emotional cue data, and characterised in that the software directs the at least one processor to further carry out a calibration of the classifier for a target individual by supplementing the training data set with at least one image of the target individual and a corresponding user provided label of the emotional cue of the target individual and retraining the classifier for the target individual using the emotional cue and the corresponding label of the emotional cue of the target individual. obtain data (103, 202) comprising a sequence of images captured by the at least one camera; detect a face for at least one person within a plurality of images in the sequence of images; detect at least one emotional cue in the face based upon the plurality of images using a classifier; identify at least one emotion based on the emotional cue; and display at least one emotion indicator label in real time to provide therapeutic feedback; wherein the classifier is trained using a training data set of statistically representative emotional cue data, and characterised in that the software directs the at least one processor to further carry out a calibration of the classifier for a target individual by supplementing the training data set with at least one image of the target individual and a corresponding user provided label of the emotional cue of the target individual and retraining the classifier for the target individual using the emotional cue and the corresponding label of the emotional cue of the target individual.