Victor Sardenberg

Read it here. Computational Quantitative Aesthetics Evaluation: Evaluating architectural images using computer vision, machine learning and social media Victor Sardenberg & Mirco Becker This paper correlates two methods of aesthetic evaluation of architectural images utilising computer vision (CV) and machine learning (ML) for automating aesthetic evaluation: Calibrated aesthetic measure (CalAM) and aesthetic scoring model (ASM). From a database of images of proposals for a single location, users are invited to like or dislike it on social media to feed an ML model and calibrate an aesthetic measure formula (AMF). A possible application is to assist designers in making decisions according to the hedonic response given by users previously, enabling a faster way of popular participation. Keywords: Quantitative Aesthetics, Crowdsourcing, Aesthetic Measure, Computer Vision, Machine learning, Social Media