Abstract:
Most techniques for group emotion recognition rely on detection on faces of people and then aggregating the facial information to interpret the group emotion of a given i...View moreMetadata
Abstract:
Most techniques for group emotion recognition rely on detection on faces of people and then aggregating the facial information to interpret the group emotion of a given image. However, several faces in the image may be occluded, non-frontal, or indistinguishable, i.e., too many faces in a single image (crowd). This paper focuses on such cases and investigate alternate frameworks which does not involve face detection. The developed frameworks are applied on two datasets – EmotiC and Group Affect Database 3.0 and the results are shown to be competitive with face detection (MTCNN) based approaches.
Published in: 2019 14th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2019)
Date of Conference: 14-18 May 2019
Date Added to IEEE Xplore: 11 July 2019
ISBN Information: