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Kalpayita- A Machine Learning Approach to Interior Designing


Apoorva Jaiswal , Dayananda Sagar College of Engineering; Ashish Agarwal, Dayananda Sagar College of Engineering; Komma Karthik Reddy, Dayananda Sagar College of Engineering; Akshaya S, Dayananda Sagar College of Engineering; Dr. Krishnan R, Dayananda Sagar College of Engineering


jMonkey, Natural Language Processing, Interior Designing, Machine Learning


The existing approaches in Interior Designing do not leverage the latest technologies such as Machine Learning and are stuck with mundane methods like drag and drop approach to create a required scene. SceneSeer is one of the few existing systems which makes use of Text to 3D scene conversion approach, but it is still not used much in the field of Interior Designing. We present Kalpayita: A Voice driven tool to make Interior Designing hassle free. It converts voice to 3D scene. Voice commands in natural language allow the users, such as Interior Designers or even the people with least knowledge in this field, to interact with the system. These commands are converted into text and Natural Language Processing is applied on the text to make the system understand what the user wants. The result generated from Natural Language Processing is then fed into the jMonkeyEngine to display the 3D scene. Our system is an improvement over SceneSeer. We make use of voice commands, and our studies show that the accuracy and time complexity of our system Kalpayita is much better than the pre-existing Text to 3D scene conversion systems. Visual impact is an important aspect in Interior Designing. Likewise, our system generates 3D scenes which are better than other systems in aesthetics and looks.

Other Details

Paper ID: IJSRDV6I30847
Published in: Volume : 6, Issue : 3
Publication Date: 01/06/2018
Page(s): 1616-1619

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