  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.
