Sandplay image, as an important psychoanalysis carrier, is a visual scene constructed by the client selecting and placing sand objects (e.g., sand, river, human figures, animals, vegetation, buildings, etc.). As the projection of the client's inner world, it contains high-level semantic information reflecting the client's subjective psychological states, which is different from the common natural image scene that only contains the objective basic semantics (e.g., object's name, attribute, bounding box, etc.). In this work, we take "split" which is a typical psychological semantics related to many emotional and personality problems as the research goal, and we propose an automatic detection model, which can replace the time-consuming and expensive manual analysis process. To achieve that, we design a distribution map generation method projecting the semantic judgment problem into a visual problem, and a feature dimensionality reduction and extraction algorithm which can provide a good representation of split semantics. Besides, we built a sandplay datasets by collecting one sample from each client and inviting 5 therapists to label each sample, which has a large data cost. Experimental results demonstrated the effectiveness of our proposed method.

翻译：沙盘图像作为一种重要的心理分析载体，是来访者通过选择和放置沙具（如沙子、河流、人物、动物、植被、建筑等）构建的视觉场景。作为来访者内心世界的投射，它蕴含着反映来访者主观心理状态的高层语义信息，这与仅包含客观基础语义（如物体名称、属性、边界框等）的常见自然图像场景不同。本研究以与多种情绪及人格问题相关的典型心理语义——“分裂”为研究目标，提出了一种自动检测模型，可替代耗时且昂贵的人工分析过程。为此，我们设计了一种分布图生成方法，将语义判断问题转化为视觉问题；同时提出了一种特征降维与提取算法，能够有效表征分裂语义。此外，我们通过从每位来访者处收集一个样本，并邀请5位治疗师对每个样本进行标注，构建了沙盘数据集，其数据成本较高。实验结果表明了所提方法的有效性。