Dynamic Emotional Faces Generalise Better to a New Expression but not to a New View
Authors: Liu, C.H., Chen, W., Ward, J. and Takahashi, N.
Journal: Scientific Reports
Volume: 6
eISSN: 2045-2322
DOI: 10.1038/srep31001
Abstract:Prior research based on static images has found limited improvement for recognising previously learnt faces in a new expression after several different facial expressions of these faces had been shown during the learning session. We investigated whether non-rigid motion of facial expression facilitates the learning process. In Experiment 1, participants remembered faces that were either presented in short video clips or still images. To assess the effect of exposure to expression variation, each face was either learnt through a single expression or three different expressions. Experiment 2 examined whether learning faces in video clips could generalise more effectively to a new view. The results show that faces learnt from video clips generalised effectively to a new expression with exposure to a single expression, whereas faces learnt from stills showed poorer generalisation with exposure to either single or three expressions. However, although superior recognition performance was demonstrated for faces learnt through video clips, dynamic facial expression did not create better transfer of learning to faces tested in a new view. The data thus fail to support the hypothesis that non-rigid motion enhances viewpoint invariance. These findings reveal both benefits and limitations of exposures to moving expressions for expression-invariant face recognition.
https://eprints.bournemouth.ac.uk/24488/
Source: Scopus
Dynamic Emotional Faces Generalise Better to a New Expression but not to a New View.
Authors: Liu, C.H., Chen, W., Ward, J. and Takahashi, N.
Journal: Sci Rep
Volume: 6
Pages: 31001
eISSN: 2045-2322
DOI: 10.1038/srep31001
Abstract:Prior research based on static images has found limited improvement for recognising previously learnt faces in a new expression after several different facial expressions of these faces had been shown during the learning session. We investigated whether non-rigid motion of facial expression facilitates the learning process. In Experiment 1, participants remembered faces that were either presented in short video clips or still images. To assess the effect of exposure to expression variation, each face was either learnt through a single expression or three different expressions. Experiment 2 examined whether learning faces in video clips could generalise more effectively to a new view. The results show that faces learnt from video clips generalised effectively to a new expression with exposure to a single expression, whereas faces learnt from stills showed poorer generalisation with exposure to either single or three expressions. However, although superior recognition performance was demonstrated for faces learnt through video clips, dynamic facial expression did not create better transfer of learning to faces tested in a new view. The data thus fail to support the hypothesis that non-rigid motion enhances viewpoint invariance. These findings reveal both benefits and limitations of exposures to moving expressions for expression-invariant face recognition.
https://eprints.bournemouth.ac.uk/24488/
Source: PubMed
Dynamic Emotional Faces Generalise Better to a New Expression but not to a New View
Authors: Liu, C.H., Chen, W., Ward, J. and Takahashi, N.
Journal: SCIENTIFIC REPORTS
Volume: 6
ISSN: 2045-2322
DOI: 10.1038/srep31001
https://eprints.bournemouth.ac.uk/24488/
Source: Web of Science (Lite)
Dynamic Emotional Faces Generalise Better to a New Expression but not to a New View
Authors: Liu, C., Chen, W., Ward, J. and Takahashi, N.
Journal: Scientific Reports
Publisher: Nature Publishing Group: Open Access Journals - Option C
ISSN: 2045-2322
DOI: 10.1038/srep31001
Abstract:Prior research based on static images has found limited improvement for recognising previously learnt faces in a new expression after several different facial expressions of these faces had been shown during the learning session. We investigated whether non-rigid motion of facial expression facilitates the learning process. In Experiment 1, participants remembered faces that were either presented in short video clips or still images. To assess the effect of exposure to expression variation, each face was either learnt through a single expression or three different expressions. Experiment 2 examined whether learning faces in video clips could generalise more effectively to a new view. The results show that faces learnt from video clips generalised effectively to a new expression with exposure to a single expression, whereas faces learnt from stills showed poorer generalisation with exposure to either single or three expressions. However, although superior recognition performance was demonstrated for faces learnt through video clips, dynamic facial expression did not create better transfer of learning to faces tested in a new view. The data thus fail to support the hypothesis that non-rigid motion enhances viewpoint invariance. These findings reveal both benefits and limitations of exposures to moving expressions for expression-invariant face recognition.
https://eprints.bournemouth.ac.uk/24488/
Source: Manual
Dynamic Emotional Faces Generalise Better to a New Expression but not to a New View.
Authors: Liu, C.H., Chen, W., Ward, J. and Takahashi, N.
Journal: Scientific reports
Volume: 6
Pages: 31001
eISSN: 2045-2322
ISSN: 2045-2322
DOI: 10.1038/srep31001
Abstract:Prior research based on static images has found limited improvement for recognising previously learnt faces in a new expression after several different facial expressions of these faces had been shown during the learning session. We investigated whether non-rigid motion of facial expression facilitates the learning process. In Experiment 1, participants remembered faces that were either presented in short video clips or still images. To assess the effect of exposure to expression variation, each face was either learnt through a single expression or three different expressions. Experiment 2 examined whether learning faces in video clips could generalise more effectively to a new view. The results show that faces learnt from video clips generalised effectively to a new expression with exposure to a single expression, whereas faces learnt from stills showed poorer generalisation with exposure to either single or three expressions. However, although superior recognition performance was demonstrated for faces learnt through video clips, dynamic facial expression did not create better transfer of learning to faces tested in a new view. The data thus fail to support the hypothesis that non-rigid motion enhances viewpoint invariance. These findings reveal both benefits and limitations of exposures to moving expressions for expression-invariant face recognition.
https://eprints.bournemouth.ac.uk/24488/
Source: Europe PubMed Central
Dynamic Emotional Faces Generalise Better to a New Expression but not to a New View
Authors: Liu, C., Chen, W., Ward, J. and Takahashi, N.
Journal: Scientific Reports
Volume: 6
Pages: 31001
ISSN: 2045-2322
Abstract:Prior research based on static images has found limited improvement for recognising previously learnt faces in a new expression after several different facial expressions of these faces had been shown during the learning session. We investigated whether non-rigid motion of facial expression facilitates the learning process. In Experiment 1, participants remembered faces that were either presented in short video clips or still images. To assess the effect of exposure to expression variation, each face was either learnt through a single expression or three different expressions. Experiment 2 examined whether learning faces in video clips could generalise more effectively to a new view. The results show that faces learnt from video clips generalised effectively to a new expression with exposure to a single expression, whereas faces learnt from stills showed poorer generalisation with exposure to either single or three expressions. However, although superior recognition performance was demonstrated for faces learnt through video clips, dynamic facial expression did not create better transfer of learning to faces tested in a new view. The data thus fail to support the hypothesis that non-rigid motion enhances viewpoint invariance. These findings reveal both benefits and limitations of exposures to moving expressions for expression-invariant face recognition.
https://eprints.bournemouth.ac.uk/24488/
Source: BURO EPrints