"Title: Equirectangular 360° Image Dataset for Detecting Reusable Construction Components
Authors: Bendiek Laranjo, Ana (1,2);
Hunhevicz, Jens J. (1,2);
Menzel, Karsten (3);
De Wolf, Catherine (2)
Affiliation: 1: Empa, Dübendorf, Switzerland;
2: ETH Zürich, Zurich, Switzerland;
3: Technische Universität Dresden, Dresden, Germany
Keywords: circular economy, building construction, computer vision, real-world dataset, 360-degree panorama
Session: Data Sensing & Acquisition
Paper Link: 10.35490/EC3.2024.266
Abstract: Insufficient as-built data hinders the transition of the architecture, engineering, and construction (AEC) sector to a circular system. Combining reality capture and machine learning (ML) could help better detect reusable components. However, a comprehensive image dataset of on-site inventory for circular economy strategies has yet to be developed. This study introduces and describes the generation of a purpose-built, 360° dataset. Initial validation using the YOLOv8 object detection model demonstrates a 63.4% mean average precision (mAP50), making it viable for computer vision. Further exploration of automating building stock inventory using 360-degree images and ML for urban mining is needed."
