Sketch mapping is widely used in crime scene investigation (CSI) to document, interpret, and communicate spatial information. However, it is typically performed on 2D media, which limits its ability to represent 3D spatial relationships. We present HolmeSketcher, a generative 3D sketch mapping system that combines a front-end 3D drawing interface with a back-end deep learning pipeline to support object generation and scene reconstruction in extended reality. In a within-subject user study (N = 15), HolmeSketcher improved the spatial accuracy and interpretability of reconstructed scenes, but with a clear trade-off of higher task load and lower usability compared with paper-based 2D sketch mapping. By integrating findings from the user study and expert interviews (N = 3), we further derive three design implications for next-generation 3D sketch mapping tools for CSI.

翻译：草图映射广泛用于犯罪现场调查（CSI）中记录、解释和传递空间信息。然而，该过程通常在二维媒介上进行，这限制了其表达三维空间关系的能力。我们提出了HolmeSketcher——一种生成式三维草图映射系统，该系统将前端三维绘图界面与后端深度学习管线相结合，以支持扩展现实中的物体生成与场景重建。在受试者内用户研究（N=15）中，HolmeSketcher提升了重建场景的空间准确性与可解释性，但相较于纸质二维草图映射，也显著增加了任务负荷并降低了可用性。通过整合用户研究与专家访谈（N=3）的发现，我们进一步推导出面向下一代CSI三维草图映射工具的三种设计启示。