Nonverbal Interpersonal Communication Exploration Toolbox
Aleksandr Evgrashin, Carolin Schmitt, Timo Lübbing, Ashutosh Jha, Buket Naz Zeren, Sophie Bauer, Gökce Ergün, Senya Polikovsky
NICE Toolbox is an easy-to-use framework for exploring nonverbal human communication. It aims to enable the investigation of observable signs that reflect the mental state and behaviors of the individual. Additionally, these visual nonverbal cues reveal the interpersonal dynamics between people in face-to-face conversations.
NICE Toolbox incorporates a growing set of Computer Vision algorithms to track and identify important visual components of nonverbal communication. Existing state-of-the-art deep-learning and rule-based algorithms are combined into a single, easy-to-use software toolbox. Based on single- or multi-camera video data, it encompasses whole-body pose estimation, gaze tracking, head orientation, and facial expression for each individual as well as movement dynamics calculation (kinematics), gaze interaction monitoring (mutual-gaze), and the measurement of physical body distance between dyads. This first set of components and algorithms is going to be extended in future releases.
In future releases, we plan to extend the NICE Toolbox to include detectors for eye closure, active speaking and micro-action recognition.
Upcoming Event: One-Day Workshop
We are organizing a one-day workshop that will provide a hands-on introduction to the NICE Toolbox using example datasets and pre-configured virtual machines.
Participants will explore the software, perform analyses on sample data, and review the resulting outputs.
Dates:
- 17.11.2026 (On site Session in Tübingen)
- 20.11.2026 (Online Session)
For more information about the workshop and registration, please visit Workshop Details and Registration.
NICE in Research
Interpersonal temporal coordination refers to the alignment of signals between interacting individuals in rhythmically matched or predictably coupled patterns. Movement synchrony is a central component of this coordination, supporting effective communication, emotional attunement, and therapeutic engagement. This study uses the Nonverbal Interpersonal Communication Exploration (NICE) Toolbox (https://nice.is.tue.mpg.de/), an automated video-based software for analysing naturalistic interactions. We are using NICE to quantify interpersonal temporal coordination, specifically movement synchrony, as an indicator of interaction quality in parent–child psychotherapy [...]
The employee perception of microaggressions from workplace AI and avatars remains largely unexplored. This study examines how individuals perceive and respond to microaggressions perpetrated by humans versus avatars in hybrid work environments. We propose a controlled laboratory experiment in which participants interact with human and avatar aggressors of different genders, while collecting multimodal behavioral data (facial expressions, gaze, posture) and self-reported emotional and cognitive responses. We expect stronger emotional and physiological reactions to human-delivered microaggressions compared to those delivered by an avatar. Our findings will provide empirical insights into how people attribute social meaning to AI-driven agents and how subtle biases manifest in human–AI interactions. The study contributes to IS research by informing the design and governance of responsible workplace technologies, including avatar-based training and bias-aware communication systems.
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