Author: Haotian Xu
Publisher:
ISBN:
Category : Cities and towns
Languages : en
Pages : 86
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Book Description
3D urban reconstruction is an active research area which is significant for many applications, such as virtual tours and urban planning. 3D facade reconstruction is a fundamental task in this research area. 3D real-time LiDAR is an ideal choice for capturing the 3D data in large-scale 3D urban reconstruction because of its fast working speed and mobility. However, the resulting 3D point cloud is very sparse and is not directly suitable for 3D reconstruction. In this paper, we aim to provide a new method for 3D facade reconstruction, which is based on the fusion of 3D terrestrial LiDAR and images. Our novelty lies in the extraction of semantic information from images and a state-of-the-art depth completion method used to estimate the missing depth information in LiDAR scans. The basic idea of our 3D facade reconstruction method is an iterative optimization process of sparse depth maps. More specifically, the input LiDAR point cloud is first converted to a depth map of the input image. Then, facade elements made of glass (e.g., windows) are extracted by using an instance segmentation technique. Once these elements are located, their exact depth values can be estimated by using weak architectural constraints. Finally, a data-driven depth completion methods based on CNN is used for predicting the rest of missing depth data in the semi-dense depth map, which generates the final completed dense depth map. Besides, we present a new dataset used for 3D facade reconstruction. The dataset contains LiDAR scans and images of the 15 different facades in the City Campus of the University of Auckland. All the 2D and 3D data in this dataset are calibrated. The proposed 3D facade reconstruction method was evaluated on this new dataset. The experimental results show that our approach can generate photorealistic 3D reconstruction models for some particular styles of facades. Also, our method is able to identify facade elements such as windows and doors to enhance 3D models of buildings semantically.
Author: Chilwoo Lee
Publisher: Springer Nature
ISBN: 3030348792
Category : Computers
Languages : en
Pages : 418
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Book Description
This book constitutes the conference proceedings of the 9th Pacific Rim Symposium on Image and Video Technology, PSIVT 2019, held in Sydney, NSW, Australia, in November 2019. A total of 31 papers were carefully reviewed and selected from 55 submissions. The main conference comprises 11 major subject areas that span the field of image and video technology, namely imaging and graphics hardware and visualization, image/video coding and transmission, image/video processing and analysis, image/video retrieval and scene understanding, applications of image and video technology, biomedical image processing and analysis, biometrics and image forensics, computational photography and arts, computer and robot vision, pattern recognition, and video surveillance.
Author: Prakash Duraisamy
Publisher:
ISBN:
Category : Image processing
Languages : en
Pages : 78
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Book Description
Author: Martin Weinmann
Publisher: Springer
ISBN: 3319292463
Category : Computers
Languages : en
Pages : 250
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Book Description
This unique work presents a detailed review of the processing and analysis of 3D point clouds. A fully automated framework is introduced, incorporating each aspect of a typical end-to-end processing workflow, from raw 3D point cloud data to semantic objects in the scene. For each of these components, the book describes the theoretical background, and compares the performance of the proposed approaches to that of current state-of-the-art techniques. Topics and features: reviews techniques for the acquisition of 3D point cloud data and for point quality assessment; explains the fundamental concepts for extracting features from 2D imagery and 3D point cloud data; proposes an original approach to keypoint-based point cloud registration; discusses the enrichment of 3D point clouds by additional information acquired with a thermal camera, and describes a new method for thermal 3D mapping; presents a novel framework for 3D scene analysis.
Author: Marc Racicot
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
Author: Karim Hammoudi
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Book Description
The aim of this work is to develop research on 3D building modeling. In particular, the research in aerial-based 3D building reconstruction is a topic very developed since 1990. However, it is necessary to pursue the research since the actual approaches for 3D massive building reconstruction (although efficient) still encounter problems in generalization, coherency, accuracy. Besides, the recent developments of street acquisition systems such as Mobile Mapping Systems open new perspectives for improvements in building modeling in the sense that the terrestrial data (very dense and accurate) can be exploited with more performance (in comparison to the aerial investigation) to enrich the building models at facade level (e.g., geometry, texturing).Hence, aerial and terrestrial based building modeling approaches are individually proposed. At aerial level, we describe a direct and featureless approach for simple polyhedral building reconstruction from a set of calibrated aerial images. At terrestrial level, several approaches that essentially describe a 3D urban facade modeling pipeline are proposed, namely, the street point cloud segmentation and classification, the geometric modeling of urban facade and the occlusion-free facade texturing.
Author: Shi Pu
Publisher:
ISBN: 9789061642886
Category : Buildings
Languages : en
Pages : 119
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Book Description
Author: Conglin Huang
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
Author: Michael Ying Yang
Publisher: Academic Press
ISBN: 0128173599
Category : Technology & Engineering
Languages : en
Pages : 424
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Book Description
Multimodal Scene Understanding: Algorithms, Applications and Deep Learning presents recent advances in multi-modal computing, with a focus on computer vision and photogrammetry. It provides the latest algorithms and applications that involve combining multiple sources of information and describes the role and approaches of multi-sensory data and multi-modal deep learning. The book is ideal for researchers from the fields of computer vision, remote sensing, robotics, and photogrammetry, thus helping foster interdisciplinary interaction and collaboration between these realms. Researchers collecting and analyzing multi-sensory data collections – for example, KITTI benchmark (stereo+laser) - from different platforms, such as autonomous vehicles, surveillance cameras, UAVs, planes and satellites will find this book to be very useful. - Contains state-of-the-art developments on multi-modal computing - Shines a focus on algorithms and applications - Presents novel deep learning topics on multi-sensor fusion and multi-modal deep learning
Author: Chuan-Yu Chang
Publisher: Springer
ISBN: 9811391904
Category : Computers
Languages : en
Pages : 795
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Book Description
The present book includes extended and revised versions of papers presented during the 2018 International Computer Symposium (ICS 2018), held in Yunlin, Republic of China (Taiwan), on December 20-22, 2018. The 86 papers presented were carefully reviewed and selected from 263 submissions from 11 countries. The variety of the topics include machine learning, sensor devices and platforms, sensor networks, robotics, embedded systems, networks, operating systems, software system structures, database design and models, multimedia and multimodal retrieval, object detection, image processing, image compression, mobile and wireless security.
