Susana Ruano

Trinity College Dublin | TCD · School of Computer Science and Statistics

We present a study of image-based 3D reconstruction methods that use aerial images in large-scale metropolitan areas. Specifically, the study analyzes both open-source methods from the state of the art, and some of the most used commercial photogrammetry applications. The performance of these methods is measured against the densest annotated LiDAR...

We present a study of image-based 3D reconstruction methods that use aerial images in large-scale metropolitan areas. Specifically, the study analyzes both open-source methods from the state of the art, and some of the most used commercial photogrammetry applications. The performance of these methods is measured against the densest annotated LiDAR...

Neural Radiance Fields (NeRF) is a recent technology which had a large impact in computer vision, promising to generate high quality novel views and corresponding disparity map, all using a fairly small number of input images. In effect, they are a new way to represent a light field. In this paper, we compare NeRF with traditional light field metho...

Current human digitization techniques from a single image are showing promising results when it comes to the quality of the estimated geometry, but they often fall short when it comes to the texture of the generated 3D model, especially on the occluded side of the person, while some others do not even output a texture for the model. Our goal in thi...

This paper presents a novel benchmark to evaluate 3D reconstruction methods using aerial images in a large-scale urban scenario. In particular, it presents an evaluation of open-source state-of-the-art pipelines for image-based 3D reconstruction including, for the first time, an analysis per urban object category. Therefore, the standard evaluation...

As a rapidly growing medium, volumetric video is gaining attention beyond academia, reaching industry and creative communities alike. This brings new challenges to reduce the barrier to entry from a technical and economical point of view. We present a system for robustly and autonomously performing temporally coherent tracking for volumetric sequen...

Scene understanding of full-scale 3D models of an urban area remains a challenging task. While advanced computer vision techniques offer cost-effective approaches to analyse 3D urban elements, a precise and densely labelled dataset is quintessential. The paper presents the first-ever labelled dataset for a highly dense Aerial Laser Scanning (ALS) p...

Scene understanding of full-scale 3D models of an urban area remains a challenging task. While advanced computer vision techniques offer cost-effective approaches to analyse 3D urban elements, a precise and densely labelled dataset is quintessential. The paper presents the first-ever labelled dataset for a highly dense Aerial Laser Scanning (ALS) p...

Unmanned Aerial Vehicles (UAVs) are being extensively used nowadays. Therefore, pilots of traditional aerial platforms should adapt their skills to operate them from a Ground Control Station (GCS). Common GCSs provide information in separate screens: one presents the video stream while the other displays information about the mission plan and infor...

This paper presents a registration method for images with global illumination variations. The method is based on a joint iterative optimization (geometric and photometric) of the L 1 norm of the intensity error. Two strategies are compared to directly find the appropriate intensity transformation within each iteration: histogram specification and t...

In the context of aerial imagery, one of the first steps toward a coherent processing of the information contained in multiple images is geo-registration, which consists in assigning geographic 3D coordinates to the pixels of the image. This enables accurate alignment and geo-positioning of multiple images, detection of moving objects and fusion of...