🤖 AI Summary
This work proposes the first extended reality (XR)-based animation authoring framework tailored for criminal investigation applications, addressing the challenge that existing animation tools are ill-suited for non-expert forensic personnel to efficiently reconstruct and validate dynamic crime scenes. Developed through close collaboration with criminology experts, the system features an intuitive, low-barrier interface that enables users without 3D modeling experience to rapidly create and observe animated reconstructions of criminal events. Evaluated by 18 participants—including six trained criminology professionals—the system demonstrates high task completion rates and strong usability scores in character animation tasks, effectively supporting diverse use cases such as hypothesis validation, case presentation, situational understanding, and training.
📝 Abstract
Law enforcement authorities are increasingly interested in 3D modelling for virtual crime scene reconstruction, enabling offline analysis without the cost and contamination risk of on-site investigation. Past work has demonstrated spatial relationships through static modelling but validating the sequence of events in dynamic scenarios is crucial for solving a case. Yet, animation tools are not well suited to crime scene reconstruction, and complex for non-experts in 3D modelling/animation. Through a co-design process with criminology experts, we designed"Criminator"-a methodological framework and XR tool that simplifies animation authoring. We evaluated this tool with participants trained in criminology (n=6) and untrained individuals (n=12). Both groups were able to successfully complete the character animation tasks and provided high usability ratings for observation tasks. Criminator has potential for hypothesis testing, demonstration, sense-making, and training. Challenges remain in how such a tool fits into the entire judicial process, with questions about including animations as evidence.