An automatic mosaicking method for building facade texture mapping using a monocular close-range image sequence

Zhang, Kang; Zhang, Liqiang; Zlatanova, Sisi; Li, Jonathan

doi:10.1016/j.isprsjprs.2009.11.003

Cited by 19 publications

(15 citation statements)

References 22 publications

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“…In remote sensing, this technique is applied to different datasets, including satellite [1][2][3], aerial [4][5][6][7], low-altitude [8,9] and close-range [10,11] images. In a typical processing pipeline, aerial images are always reprojected onto a digital terrain model (DTM) with various camera locations and orientations, and the obtained digital orthophoto maps (DOMs) are used for mosaicking [12].…”

Section: Introductionmentioning

confidence: 99%

Automatic Seamline Network Generation for Urban Orthophoto Mosaicking with the Use of a Digital Surface Model

Chen

Sun

et al. 2014

Remote Sensing

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Intelligent seamline selection for image mosaicking is an area of active research in the fields of massive data processing, computer vision, photogrammetry and remote sensing. In mosaicking applications for digital orthophoto maps (DOMs), the visual transition in mosaics is mainly caused by differences in positioning accuracy, image tone and relief displacement of high ground objects between overlapping DOMs. Among these three factors, relief displacement, which prevents the seamless mosaicking of images, is relatively more difficult to address. To minimize visual discontinuities, many optimization algorithms have been studied for the automatic selection of seamlines to avoid high ground objects. Thus, a new automatic seamline selection algorithm using a digital surface model (DSM) is proposed. The main idea of this algorithm is to guide a seamline toward a low area on the basis of the elevation information in a DSM. Given that the elevation of a DSM is not completely synchronous with a DOM, a new model, called the orthoimage elevation synchronous model (OESM), is derived and introduced. OESM can accurately reflect the elevation information for each DOM unit. Through the morphological processing of the OESM data in the overlapping area, an initial path network is obtained for seamline selection. Subsequently, a cost function is defined on the basis of several measurements, and Dijkstra's algorithm is adopted to determine the least-cost path from the initial network. Finally, the proposed algorithm is employed for automatic seamline network construction; the effective mosaic polygon of each image is determined, and a seamless mosaic is generated. The experiments with three different datasets indicate that the proposed method OPEN ACCESS Remote Sens. 2014, 6 12335 meets the requirements for seamline network construction. In comparative trials, the generated seamlines pass through fewer ground objects with low time consumption.

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Section: Introductionmentioning

confidence: 99%

Automatic Seamline Network Generation for Urban Orthophoto Mosaicking with the Use of a Digital Surface Model

Chen

Sun

et al. 2014

Remote Sensing

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“…[GKVH09]. There are further fully automatic attempts (most of them in the photogrammetry literature) which aim at projective texture generation for existing building models [CT99, WH01, WTT*02, BÖ4, OR05, GKKP07, TL07, TKO08, KZZL10].…”

Section: Façades and Imagesmentioning

confidence: 99%

A Survey of Urban Reconstruction

Weiss

Wonka

Aliaga

et al. 2013

Computer Graphics Forum

381

259

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This paper provides a comprehensive overview of urban reconstruction. While there exists a considerable body of literature, this topic is still under active research. The work reviewed in this survey stems from the following three research communities: computer graphics, computer vision and photogrammetry and remote sensing. Our goal is to provide a survey that will help researchers to better position their own work in the context of existing solutions, and to help newcomers and practitioners in computer graphics to quickly gain an overview of this vast field. Further, we would like to bring the mentioned research communities to even more interdisciplinary work, since the reconstruction problem itself is by far not solved.

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“…For each reference line segment li, we may obtain several candidate segments( Figure 6), which are defined as set Ai and are judged by distance (δ ) and direction (δ ) constraints based on Equation (1).…”

Section: Searching For Candidate Adjacent Segmentsmentioning

confidence: 99%

“…The OPEN ACCESS faç ade is always extracted based on ground data from on-board cameras [1] or terrestrial laser scanners [2]. Airborne platforms have the advantages of low cost, high efficiency, wide coverage and extensive applicability.…”

Section: Introductionmentioning

confidence: 99%

Building Façade Recognition Using Oblique Aerial Images

et al. 2015

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This study proposes a method to recognize faç ades from large-scale urban scenes based on multi-level image features utilizing a recently developed oblique aerial photogrammetry technique. The method involves the use of multi-level image features, a bottom-up feature extraction procedure to produce regions of interest through monoscopic analysis, and then a coarse-to-fine feature matching strategy to characterise and match the regions in a stereoscopic model. Feature extraction from typical urban Manhattan scenes is based on line segments. Windows are re-organised based on the spatial constraints of line segments and the homogeneous structure of the spectrum. Façades as regions of interest are successfully constructed with a remarkable single edge and evidence from windows to get rid of occlusion. Feature matching is hierarchically performed beginning from distinctive facades and regularly distributed windows to the sub-pixel point primitives. The proposed strategy can effectively solve ambiguity and multi-solution problems in the complex urban scene matching process, particularly repetitive and poor-texture façades in oblique view.

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An automatic mosaicking method for building facade texture mapping using a monocular close-range image sequence

Cited by 19 publications

References 22 publications

Automatic Seamline Network Generation for Urban Orthophoto Mosaicking with the Use of a Digital Surface Model

Automatic Seamline Network Generation for Urban Orthophoto Mosaicking with the Use of a Digital Surface Model

A Survey of Urban Reconstruction

Building Façade Recognition Using Oblique Aerial Images

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