A Novel Edge Detection Operator for Identifying Buildings in Augmented Reality Applications
This work addresses a domain-specific challenge for augmented reality applications in fields like tourism and culture, but it appears incremental as it builds on existing edge detection methods.
The paper tackles the problem of precise building detection in augmented reality by proposing a novel edge detection filter that emphasizes vertical and horizontal edges, resulting in improved extraction of building contours and facade features.
Augmented Reality is an environment-enhancing technology, widely applied in many domains, such as tourism and culture. One of the major challenges in this field is precise detection and extraction of building information through Computer Vision techniques. Edge detection is one of the building blocks operations for many feature extraction solutions in Computer Vision. AR systems use edge detection for building extraction or for extraction of facade details from buildings. In this paper, we propose a novel filter operator for edge detection that aims to extract building contours or facade features better. The proposed filter gives more weight for finding vertical and horizontal edges that is an important feature for our aim.