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

Abstract

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.

Artificial Faces Predict Gaze Allocation in Complex Dynamic Scenes

“…Face inversion disrupts this process leading face recognition accuracies to drastically decline when inverted faces are presented (Yin, 1969). While the vast majority of studies examined face processing in two-dimensional faces, it was recently reported that recognition is improved for 3D vs. 2D faces but not when they are inverted (Eng et al, 2017). This refined recognition is likely due to improved holistic processing when faces are more realistic and depth information is enriched.…”

Introducing the FIDENTIS 3D Face Database

“…A three-dimensional representation allows for the display and processing of all three dimensions of a face equally and without one of them being discarded or distorted. It compensates for the lack of depth in traditional photographs, which creates difficulties for recognizing faces in a holistic manner, and reduces the ability to ascertain the topography of separate facial features (Eng et al 2017). Ultimately, given an easy conversion between 3D and 2D data, it provides a good starting point for the examination of both 3D and 2D faces and face-related processes (Ferková et al 2017).…”

Do 3D face images capture cues of strength, weight, and height better than 2D face images do?

“…These studies suggest strength, weight, and height can be judged somewhat accurately from face images, but no studies have yet directly compared the effect of stimulus type (2D versus 3D face images) on the accuracy of perceptions of these (or any other) traits. While some previous work has used both 2D and 3D images, these studies have focused on testing attractiveness and formidability ratings only (Tigue et al, 2012;Trebicky et al, 2018), or similarities in face recognition (e.g., Eng et al, 2017) and morphological measurements (e.g., Hill et al, 2017).…”