Towards an Automated Home Interior Designer System

摘要

We present an almost completely automated intelligent system that produces realistic and aesthetically appealing interior designs for homes. We present the results from our current implementation that generates interior designs for rectangular living rooms. The particularly striking feature of our system is that it generates multiple plausible options for an empty room. The relationships between different elements of a room and items placed in the room are represented as Bayesian networks. The causal relationships defining the network structure are derived from standard thumbrules of interior designing. The parameters for every node in the network are learnt from information extracted semi-automatically from the top view images of furnished living rooms and conversation areas. New layouts based on user inputs are generated upon inferencing from this learnt network. We have successfully dealt with living rooms having (i) dimensions varying from 9 to 25 ft, (ii) 1-3 doors, (Hi) 2 windows, (iv) TV or/and fireplace as focal points, (v) dining area, (vi) second conversation area.