Bitbox: Behavioral Imaging Toolbox for Computational Analysis of Behavior from Videos
Evangelos Sariyanidi, Gokul Nair, Lisa Yankowitz, Casey J. Zampella, Mohan Kashyap Pargi, Aashvi Manakiwala, Maya McNealis, John D. Herrington, Jeffrey Cohn, Robert T. Schultz, Birkan Tunc

TL;DR
Bitbox is an open-source toolkit that simplifies the use of AI-based video analysis for behavioral research, making advanced computational measurements accessible to scientists without engineering expertise.
Contribution
It introduces a modular, validated, and user-friendly platform that bridges the gap between AI methods and behavioral science research.
Findings
Validated on clinical samples for accuracy
Provides high-level behavioral metrics from videos
Designed for easy integration and extension
Abstract
Computational measurement of human behavior from video has recently become feasible due to major advances in AI. These advances now enable granular and precise quantification of facial expression, head movement, body action, and other behavioral modalities and are increasingly used in psychology, psychiatry, neuroscience, and mental health research. However, mainstream adoption remains slow. Most existing methods and software are developed for engineering audiences, require specialized software stacks, and fail to provide behavioral measurements at a level directly useful for hypothesis-driven research. As a result, there is a large barrier to entry for researchers who wish to use modern, AI-based tools in their work. We introduce Bitbox, an open-source toolkit designed to remove this barrier and make advanced computational analysis directly usable by behavioral scientists and clinical…
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Taxonomy
TopicsEmotion and Mood Recognition · Digital Mental Health Interventions · Face Recognition and Perception
