ConductVision Face
Facial expression analysis for research labs
FACS-grade analysis, processed on your own lab machines and synced to a cloud dashboard for cross-lab work. IRB-friendly by design.
Why labs choose it
IRB-friendly local processing
Face video is analyzed on the lab machine. Raw footage never leaves your network.
20 FACS Action Units, 7 emotions
Per-frame Action Unit intensities, basic emotion probabilities, valence and arousal, exportable for SPSS or R.
Cloud dashboard for collaboration
Only derived numerical timeseries sync. Share results across labs without sharing video.
How the data flows
A small local agent processes recorded sessions on the lab machine. Action Unit and emotion timeseries sync to the ConductScience cloud dashboard for visualization, comparison, and export. Raw face video stays on-prem.
Built on py-feat (Cheong et al., 2023)
Action Unit and emotion classification use py-feat, a peer-reviewed open-source FACS toolbox validated on standard psychology datasets. We provide a downloadable methodology document covering model choices, validation, and recommended study protocols.
Cheong, J. H. et al. (2023). Py-Feat: Python Facial Expression Analysis Toolbox. Affective Science.
Where it is used
Psychology research
Quantify expressive behavior in studies of emotion regulation, social cognition, and developmental psychology.
UX research
Capture continuous emotional response during product walkthroughs without verbal interruption.
Market research
Measure reaction to creative, packaging, or product concepts with frame-level granularity.
Education research
Study classroom engagement and affect during learning interventions.
Request a demo
A walkthrough on your study design. Academic, site, hardware, and clinical configurations available; pricing on request.
Be first in line
We are taking on a small set of pilot labs. Join the waitlist for early-access pricing and quarterly product updates.
