Abstract:
The inherently rapid and subtle changes in micro-expressions pose significant challenges for micro-expression recognition (MER). Previous methods, typically relying on fr...Show MoreMetadata
Abstract:
The inherently rapid and subtle changes in micro-expressions pose significant challenges for micro-expression recognition (MER). Previous methods, typically relying on frame aggregation or optical flow, struggle to accurately capture subtle changes because of low frame rate. In this paper, we propose an Event-driven Spatio-temporal Motion Enhancement Network, which incorporates event signals captured by an event camera, to assist MER. Specifically, we introduce an Event-Enhanced Motion Extractor module to exploit event signals’ high temporal resolution property, enhancing subtle motion details. We also propose an Event-Guided Attention module to focus on subtle changes in specific areas, capturing more precise spatial features of micro-expressions. Experimental results on synthetic and real-world datasets demonstrate the superiority of our method on MER, showcasing its strong ability to capture subtle motion changes.
Date of Conference: 15-19 July 2024
Date Added to IEEE Xplore: 30 September 2024
ISBN Information: