Lim, Ken Yoong2023-06-152023-06-152023-06-14vt_gsexam:38060http://hdl.handle.net/10919/115427In historical photo research, the presence of painted backdrops have the potential to help identify subjects, photographers, locations, and jl{events surrounding} certain photographs. Yet, research processes around these backdrops are poorly documented, with no known tools to aid in the task. We propose a four-step human-AI collaboration workflow to support the jl{discovery} and clustering of these backdrops. Focusing on the painted backdrops of the American Civil War (1861 -- 1865), we present Backdrop Explorer, a content-based image retrieval (CBIR) system incorporating computer vision and novel user interactions. We evaluated Backdrop Explorer on nine users of diverse experience levels and found that all were able to effectively utilize Backdrop Explorer to find photos with similar backdrops. We also document current practices and pain points in Civil War backdrop research through user interviews. Finally, we discuss how our findings and workflow can be applied to other topics and domains.ETDenIn CopyrightHuman-AI InteractionComputer VisionContent-Based Image RetrievalDigital HumanitiesThesis