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Humans are pretty good at looking at a single two-dimensional image and understanding the full three-dimensional scene that it captures. Artificial intelligence agents are not.
Mountain disaster scenes usually contains various geographical entities, which are dynamic and complicated. Therefore, the construction of mountain disaster 3D scenes has great significance for disast...
In this work, we report a novel way of generating ground truth dataset for analyzing point cloud from different sensors and the validation of algorithms. Instead of directly labeling large amount of 3...
This paper presents our work on automated classification of Mobile Laser Scanning (MLS) point clouds of urban scenes with features derived from cylinders around points of consideration. The core of ou...
Nowadays, a huge archive of data from different satellite sensors is available for diverse objectives. While every new sensor provides data with ever higher resolution and more sophisticated special p...
This paper aims to propose and validate a methodology which can support forensic technicians while documenting a crime scene, after a contamination event (either accidental or deliberate) has changed ...
Crime scene documentation is a fundamental task which has to be undertaken in a fast, accurate and reliable way, highlighting evidence which can be further used for ensuring justice for victims and fo...
Spatial navigation is a crucial ability for living. Previous animal studies have shown that the S100B gene is causally related to spatial navigation performance in mice. However, the genetic factors i...
Publicly available benchmark data and metric evaluation approaches have been instrumental in enabling research to advance state of the art methods for remote sensing applications in urban 3D modeling....
We consider the problem of the semantic classification of 3D LiDAR point clouds obtained from urban scenes when the training set is limited. We propose a non-parametric segmentation model for urban sc...
In this paper we explore semantic segmentation of man-made scenes using fully connected conditional random field (CRF). Images of man-made scenes display strong contextual dependencies in the spatial ...
We present a system for producing multi-viewpoint panoramas of long, roughly planar scenes, such as the facades of buildings along a city street, from a relatively sparse set of photographs captured...
A new method for high resolution surface reconstruction by multi-image matching in object space is formulated with regard to the integration of a general 3-d surface model in object space, because com...
This paper describes the investigations carried out at ETH Zurich on the very-high resolution optical satellite sensor WorldView-1. The dataset includes a stereopair acquired in November 2007 over Mo...
High resolution stereo satellite imagery is well suited for the creation of digital surface models (DSM). A system for highly automated and operational DSM and orthoimage generation based on CARTOSAT...

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