3D faces are recognized more accurately and faster than 2D faces, but with similar inversion effects

• Main Authors: Eng, Derric Zeng Hong, Yick, Yee Ying, Guo, Yulan, Xu, Hong, Reiner, Miriam, Cham, Tat-Jen, Chen, Annabel Shen-Hsing
• Other Authors: School of Computer Science and Engineering
• Format: Article
• Language: English
• Published: 2020
• Subjects: Social sciences::Psychology::Consciousness and cognition; Face Recognition; Holistic Processing
• Online Access: https://hdl.handle.net/10356/138218
• Institution: Nanyang Technological University

Recognition of faces typically occurs via holistic processing where individual features are combined to provide an overall facial representation. However, when faces are inverted, there is greater reliance on featural processing where faces are recognized based on their individual features. These findings are based on a substantial number of studies using 2-dimensional (2D) faces and it is unknown whether these results can be extended to 3-dimensional (3D) faces, which have more depth information that is absent in the typical 2D stimuli used in face recognition literature. The current study used the face inversion paradigm as a means to investigate how holistic and featural processing are differentially influenced by 2D and 3D faces. Twenty-five participants completed a delayed face-matching task consisting of upright and inverted faces that were presented as both 2D and 3D stereoscopic images. Recognition accuracy was significantly higher for 3D upright faces compared to 2D upright faces, providing support that the enriched visual information in 3D stereoscopic images facilitates holistic processing that is essential for the recognition of upright faces. Typical face inversion effects were also obtained, regardless of whether the faces were presented in 2D or 3D. Moreover, recognition performances for 2D inverted and 3D inverted faces did not differ. Taken together, these results demonstrated that 3D stereoscopic effects influence face recognition during holistic processing but not during featural processing. Our findings therefore provide a novel perspective that furthers our understanding of face recognition mechanisms, shedding light on how the integration of stereoscopic information in 3D faces influences face recognition processes.