Image search engine for furniture recommendations

Abstract

Artificial intelligence (AI) has made enormous strides in recent years, transitioning from science fiction to a technology that is revolutionizing every sector of the global economy. Thanks to advances in machine learning, natural language processing and computer vision, artificial intelligence is no longer a futuristic dream, but a reality today. Once optimised and integrated into everyday life, artificial intelligence will substantially enhance human capabilities and contribute to the betterment of society. This paper will embrace the opportunities offered by computer vision, as part of artificial intelligence, by showcasing the FurnishMe application, an image search engine for furniture recommendations. Buying furniture online, as well as offline, is an overwhelming process given the quantity and diversity of furniture products available. The FurnishMe software solution allows users to easily explore the furniture of the three largest furniture retailers in Romania: Ikea, Jysk, and Dedeman. The system analyses user-uploaded interior design images in order to identify furniture items and provide aesthetically similar products from the three big retailers mentioned above. Both consumers and traders benefit from this solution. Clients benefit from a quick and easy way to choose the product they desire which integrates various features such as design, texture and colour. Moreover, businesses gain from greater sales by luring clients and saving time on in-person consultations.

Keywords

• deep learning
• convolutional neural networks
• object detection
• furniture recommendations
• web scraping
• computer vision
• visual search engine