Investigating perceptually based models to predict importance of facial blendshapes

Abstract

Blendshape facial rigs are used extensively in the industry for facial animation of virtual humans. However, storing and manipulating large numbers of facial meshes is costly in terms of memory and computation for gaming applications, yet the relative perceptual importance of blendshapes has not yet been investigated. Research in Psychology and Neuroscience has shown that our brains process faces differently than other objects, so we postulate that the perception of facial expressions will be feature-dependent rather than based purely on the amount of movement required to make the expression. In this paper, we explore the noticeability of blendshapes under different activation levels, and present new perceptually based models to predict perceptual importance of blendshapes. The models predict visibility based on commonly-used geometry and image-based metrics. CCS CONCEPTS • Applied computing → Psychology; • Computing methodologies → Mesh geometry models; • Mathematics of computing → Equational models.

The emotions effect on a virtual characters design–A student perspective analysis

“…The main difference between 2D and 3D designs is a deeper perception in the 3D models that could lead to an unconsciously more understanding of the character anatomy structure. Regarding the 3D structure and its rig, some studies using 3D designs investigated the importance of using enough amount of facial blendshapes to represent emotions digitally according to Ekman's Action Units (AU; Carrigan et al, 2020). They found some FACS more noticeable than others and established their order of importance.…”

Perception of Charisma, Comfort, Micro and Macro Expressions in Computer Graphics Characters

“…The authors found that people can distinguish between high and low confidence animations, can also associate and the gaze differences, and that the effect can be maintained for different facial expressions and scene contexts. In the work by Carrigan et al [14], the authors measured the importance of blendshapes for animating facial expressions (based on Action Units) in the perception of emotions.…”

“…Therefore, we performed the animations of facial expressions through the blendshapes of this character. The work Carrigan et al [14] showed the importance of blendshapes for the perception of facial expressions.…”