Implications of design decisions are hard to oversee for designers. This is the case in particular with respect to decisions, which influence perception related qualities of designs. Such qualities are for example visual openness, visual privacy, and spatial intimacy. They are difficult to measure because of their subjective and soft nature. Measurements of such qualities are important because they are basis for user-oriented, optimal decisions in architectural and interior design. Existing attempts in the architecture domain to assess such qualities systematically are not based on models of visual space perception. Their ability to assess perception aspects of designs is limited. In this paper a novel real-time measurement system for design is presented, which is based on a computational model of visual space perception. This perception model consists of a vision model and a space cognition model. The vision model is based on retrieval of spatial depth data in scattered form. This process is termed random direction distance sampling (RDDS). The space cognition model consists of sample-wise mapping of depth data to perception data, which is space cognition, and exponential averaging, which is a time-series analysis method, for integration of the perception data to perception information, which is the measurement outcome.