AI 中文总结
Collascope是支持拼贴式叙事的交互式系统，通过属性感知视觉检索等方法，在用户研究中助力创作者调整叙事、丰富创作，优化了素材探索体验。
AI 中文摘要
拼贴式叙事需要能支撑新兴叙事并激发创造性再解读的视觉元素，然而现有工具主要依赖基于关键词和图像的检索，对现有素材之外的偶然发现式探索支持有限。我们推出Collascope，这是一个交互式系统，可帮助创作者：（1）通过交互式元素组明确故事意图；（2）基于概念或抠图向概念和视觉维度扩展探索空间；（3）在拼贴创作的同时形成有依据、可追溯的想法。Collascope的属性感知视觉检索方法，结合与拼贴相关的视觉维度，使创作者能通过特定维度的视觉投影而非整体相似性来检索抠图。在针对传统搜索基线的被试内研究（N=12）中，参与者利用意外结果甚至素材集合的空白来调整叙事、转变基调并丰富创作，Scene Parts帮助将探索组织为可管理的子任务，参与者根据探索是由明确目标、不断发展的故事还是视觉直觉引导，以不同方式运用关联。
英文摘要
Collage-based storytelling requires visual elements that support emerging narratives and inspire creative reinterpretation. Existing tools, however, rely largely on keyword- and image-based retrieval, offering limited support for serendipitous exploration beyond existing assets. We introduce Collascope, an interactive system that helps creators (1) concretize story intent with interactive element groups, (2) expand the exploration space based on concepts or cutouts towards conceptual and visual dimensions, and (3) develop grounded, traceable ideas in parallel with collage composition. Collascope's attribute-aware visual retrieval method, instantiated with collage-relevant visual dimensions, enables creators to retrieve cutouts through dimension-specific visual projections rather than holistic similarity. In a within-subject study (N=12) against a conventional search baseline, our participants used unexpected results and even gaps in the asset collection to redirect narratives, shift tone, and enrich compositions. Scene Parts helped organize exploration into manageable subtasks, while participants used association in distinct ways depending on whether exploration was guided by a clear goal, an evolving story, or visual intuition.
CommentsTo be published at ACM UIST 2026
