Implicit Human-Centered Tagging

Abstract

This paper provides a general introduction to the concept of Implicit Human-Centered Tagging (IHCT) -the automatic extraction of tags from nonverbal behavioral feedback of media users. The main idea behind IHCT is that nonverbal behaviors displayed when interacting with multimedia data (e.g., facial expressions, head nods, etc.) provide information useful for improving the tag sets associated with the data. As such behaviors are displayed naturally and spontaneously, no effort is required from the users, and this is why the resulting tagging process is said to be "implicit". Tags obtained through IHCT are expected to be more robust than tags associated with the data explicitly, at least in terms of: generality (they make sense to everybody) and statistical reliability (all tags will be sufficiently represented). The paper discusses these issues in detail and provides an overview of pioneering efforts in the field.

Using facial expressions and peripheral physiological signals as implicit indicators of topical relevance

“…However, as discussed in [3], existing feedback techniques determine content relevance only with respect to the cognitive and situational levels of interaction, failing to acknowledge the importance of intentions, motivations and feelings in cognition and decision-making [14,34]. There is evidence that people naturally express emotion to machines and introduce a wide range of social norms and learned behaviours that guide their interactions with, and attitudes toward, interactive systems and information items [35,52,37].…”

Ensemble Nyström method for predicting conflict level from speech

“…Nonverbal communications are main concerns in social interactions. These social phenomena can be perceived and interpreted from a social and psychological point of view [1], [2]. It involves in a facet of human intelligence that plays a central role in each step of the complex social process and perhaps the most important for success in life.…”

“…This paper addresses the problem for the detection and measurement of the conflict in multiparty conversations. Conflict is recognized as one of the main dimensions along which an interaction is perceived and assessed [1]. It might be of interest in various applications in human-machine and human-human communication, such as social robot, multimedia indexing or social networks.…”

Self-Organizing Wearable Device Platform for Assisting and Reminding Humans in Real Time

“…To collect and analyze real-time activity data without the user's intentional intervention [6], a new wearable device platform is required that includes specific functions for these purposes. The platform's ability to be aware of a user's situation in real time is essential.…”