Identity-free Artificial Emotional Intelligence via Micro-Gesture Understanding
Rong Gao, Xin Liu, Bohao Xing, Zitong Yu, Bjorn W. Schuller, Heikki, K\"alvi\"ainen

TL;DR
This paper investigates unintentional micro-gestures driven by inner feelings, proposing new recognition strategies and demonstrating their positive impact on emotional understanding and related tasks.
Contribution
It introduces tailored augmentation and a spatiotemporal fusion method for micro-gesture recognition, and shows micro-gestures significantly enhance emotional AI understanding.
Findings
Achieved state-of-the-art micro-gesture recognition performance.
Micro-gestures improve emotional understanding in AI systems.
Validated methods on multiple datasets, including mainstream action datasets.
Abstract
In this work, we focus on a special group of human body language -- the micro-gesture (MG), which differs from the range of ordinary illustrative gestures in that they are not intentional behaviors performed to convey information to others, but rather unintentional behaviors driven by inner feelings. This characteristic introduces two novel challenges regarding micro-gestures that are worth rethinking. The first is whether strategies designed for other action recognition are entirely applicable to micro-gestures. The second is whether micro-gestures, as supplementary data, can provide additional insights for emotional understanding. In recognizing micro-gestures, we explored various augmentation strategies that take into account the subtle spatial and brief temporal characteristics of micro-gestures, often accompanied by repetitiveness, to determine more suitable augmentation methods.…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsHand Gesture Recognition Systems · Robotics and Automated Systems
MethodsFocus
