Implicit Human-Centered Tagging

Tagging is the annotation of multimedia data with userspecified keywords known as tags, with the aim of facilitating fast and accurate data retrieval based on these tags. In contrast to this process, also referred to as explicit tagging, implicit human-centered tagging (IHCT) refers to exploiting the information on user's nonverbal reactions (e.g., facial expressions like smiles or head gestures like shakes) to multimedia data, with which he or she interacts, to assign new or improve the existing tags associated with the target data. Thus, implicit tagging allows that a data item gets tagged each time a user interacts with it based on the reactions of the user to the data (e.g., laughter when seeing a funny video), in contrast to explicit tagging paradigm in which a data item gets tagged only if a user is requested (or chooses) to associate tags with it. As nonverbal reactions to observed multimedia are displayed naturally and spontaneously, no purposeful explicit action (effort) is required from the user; hence, the resulting tagging process is said to be "implicit" and "human centered" (in contrast to being dictated by computer and being "computer-centered").