Haptic rendering of compliance is widely used in human–computer haptic interaction. Haptic impressions of virtual objects are usually controlled through rendering algorithms and devices. However, subjective feelings of compliance are easily affected by physical properties of objects, interactive modes, and so on. So it is important to ascertain the mapping relations between controlled physical parameters and subjective perceptual feelings. In this paper, a multi-layered perceptual model was built based on psychophysical experiments to discuss these relationships in a simplified scene. Interactive signals of physical stimuli are collected by the physical receptor layer, handled by the subjective classifier layer and finally generate the evaluation results of compliance. The physical perceptual layer is used to extract useful interaction features affecting perceptual results. The subjective classifier layer is used to analyze the perceptual dimensionality of the compliance perception. The final aim of the model is to determine the mapping relationships between interaction features and dimensions of perception space. Interactive features are extracted from the interaction data collected during the exploring process, perceptual dimensionality of the compliance perception was analyzed by the factor analysis method, and relations between hierarchical layers were obtained by multi-linear regression analysis. A verification test was performed to show whether the proposed model can predict the perceptual result of new samples well. The results indicate that the model was reliable to estimate the perceptual results of compliance with an accuracy of approximately 90%. This paper may contribute a lot to the design and improvement of human-computer interaction and intelligent sensing system.