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 researchers. Bitbox is guided by principles of reproducibility, modularity, and interpretability. It provides a standardized interface for extracting high-level behavioral measurements from video, leveraging multiple face, head, and body processors. The core modules have been tested and validated on clinical samples and are designed so that new measures can be added with minimal effort. Bitbox is intended to serve both sides of the translational gap. It gives behavioral researchers access to robust, high-level behavioral metrics without requiring engineering expertise, and it provides computer scientists a practical mechanism for disseminating methods to domains where their impact is most needed. We expect that Bitbox will accelerate integration of computational behavioral measurement into behavioral, clinical, and mental health research. Bitbox has been designed from the beginning as a community-driven effort that will evolve through contributions from both method developers and domain scientists.

翻译：得益于人工智能领域的重大进展，从视频中计算测量人类行为的方法近来已变得可行。这些进展使得对面部表情、头部运动、身体动作及其他行为模态进行细粒度且精确的量化成为可能，并日益应用于心理学、精神病学、神经科学及心理健康研究中。然而，主流采用仍然缓慢。现有的大多数方法与软件是为工程领域受众开发的，需要专门的软件栈，且未能提供可直接用于假设驱动研究的行为测量水平。因此，希望在工作中使用现代AI工具的研究人员面临着巨大的入门障碍。我们推出Bitbox，一个旨在消除此障碍并使行为科学家和临床研究人员能够直接使用先进计算分析的开源工具包。Bitbox遵循可复现性、模块化和可解释性原则。它提供了一个标准化接口，用于从视频中提取高层次行为测量，并利用了多种面部、头部和身体处理器。核心模块已在临床样本上经过测试和验证，其设计使得新测量指标可以轻松添加。Bitbox旨在弥合转化鸿沟的两端：它让行为研究人员无需工程专业知识即可获取稳健的高层次行为度量，并为计算机科学家提供了一种实用的机制，以将其方法传播到最需要其影响的领域。我们期望Bitbox将加速计算行为测量在行为、临床及心理健康研究中的整合。Bitbox自设计之初便是一个社区驱动的项目，将通过方法开发者和领域科学家的贡献不断演进。