Abstract
Research on face recognition in humans has mainly relied on 2D images. This approach has certain limitations. First, observers become relatively passive in face encoding, although in reality they may be more spontaneous in exploring different views of a 3D face. Moreover, the volumetric information of a face is often confined to pictorial depth cues, making it difficult to assess the role of 3D shape processing. This paper demonstrates that 1) actively exploring different views of 3D face models produces more robust recognition memory than passively viewing playback of the same moving stimuli, 2) face matching across 2D and 3D representations typically incurs a cost, which alludes to depth-cue dependent processes in face recognition, and 3) combining multiple depth cues such as stereopsis and perspective can facilitate recognition performance even though a single depth cue alone rarely produces measurable benefits.
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Liu, C.H., Ward, J. (2005). Advantages of 3D Methods for Face Recognition Research in Humans. In: Zhao, W., Gong, S., Tang, X. (eds) Analysis and Modelling of Faces and Gestures. AMFG 2005. Lecture Notes in Computer Science, vol 3723. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11564386_19
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DOI: https://doi.org/10.1007/11564386_19
Publisher Name: Springer, Berlin, Heidelberg
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