论文标题

在沙子图像中拆分语义检测

Split Semantic Detection in Sandplay Images

论文作者

Feng, Xiaokun, Chen, Xiaotang, Jia, Jian, Huang, Kaiqi

论文摘要

Sandplay图像是重要的精神分析载体,是一个视觉场景,由客户选择和放置沙子(例如,沙子,河流,人物,动物,动物,植被,建筑物等)建造。作为客户内心世界的投影,它包含反映客户主观心理状态的高级语义信息,这与仅包含客观基本语义的常见自然图像场景不同(例如,对象的名称,属性,边界框等)。在这项工作中,我们采用“拆分”,这是一种与许多情感和人格问题有关的典型心理语义,作为研究目标,我们提出了一种自动检测模型,可以取代耗时且昂贵的手动分析过程。为了实现这一目标,我们设计了一种分发图生成方法,将语义判断问题投射到视觉问题中,以及功能维度的降低和提取算法,可以很好地表示分裂语义。此外,我们通过从每个客户端收集一个样本并邀请5位治疗师标记每个样本的标签,该数据集构建了一个SandPlay数据集,该样本具有较大的数据成本。实验结果证明了我们提出的方法的有效性。

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.

扫码加入交流群

加入微信交流群

微信交流群二维码

扫码加入学术交流群,获取更多资源