FacePipe: A Low-Cost Solution for 3D Facial Animation

Abstract

This paper presents FacePipe, a low-cost 3D facial capture and animation solution based on a conventional RGB camera and integrated with Blender. The system was developed from design requirements derived from an exploratory review, workflow analysis, and technology-selection criteria focused on low-cost hardware availability, interoperability, usability, openness, and maintainability. FacePipe consists of a MediaPipe-based capture module, a structured local data management and export workflow, and a dedicated Blender add-on that converts captured blendshape coefficients into editable animation data. The solution was evaluated through a Hierarchical Task Analysis comparing FacePipe, FaceCap, and a MetaHuman-based workflow, and through a between-subjects usability study comparing FacePipe and FaceCap with an adapted UEQ+ questionnaire. The evaluation addresses workflow structure and perceived user experience, but it does not establish objective tracking-accuracy equivalence between FacePipe and FaceCap. Results indicate that both tools were evaluated positively, but with distinct workflow profiles. FaceCap was rated more favorably in setup, perceived dependability, and Blender integration, while FacePipe showed a descriptive advantage in file export and organization and comparable perceived usability during recording. These findings suggest that FacePipe is a viable low-cost alternative for editable facial animation workflows, especially in contexts that value widely available RGB-camera-based capture, structured local file management, open implementation, and integration with Blender.