2D building change detection from high resolution satelliteimagery: A two-step hierarchical method based on 3D invariant primitives

Champion, Nicolas; Boldo, Didier; Pierrot-Deseilligny, Marc; Stamon, Georges

doi:10.1016/j.patrec.2009.10.012

Cited by 43 publications

(41 citation statements)

References 15 publications

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“…The automation of a DB diagnosis conventionally based on photointerpretation has begun more than 15 years ago (Lu et al, 1998). Several methods were proposed with different input data: satellite images (Champion et al, 2010), aerial images (Zhu et al, 2009), aerial lidar (Rutzinger et al, 2010). Other approaches use terrestrial data like panoramical images (Taneja et al, 2013) or terrestrial laser scans (Kang and Lu, 2010).…”

Section: Related Workmentioning

confidence: 99%

Quality evaluation of 3D city building Models with automatic error diagnosis

Michelin

Tierny²,

Tupin³

et al. 2013

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:Automatic building modelling allows a cost effective access to 3D semantic information of cities. However, even state-of-the-art algorithms have intrinsic limits and many errors exist in 3D reconstructions, requiring expensive manual corrections. A new approach is proposed in this paper for the automatic diagnosis of 3D building databases in urban areas. A novel error taxonomy which allows a subsequent high-level diagnosis is first proposed. Then, relevant raster and vector features are extracted from very high resolution multi-view images and Digital Surface Models so as that to retrieve such errors. In a supervised way, a set of functions is presented in order to take high-level decisions from these low-level features. Experiments on 355 buildings in an European dense city center with 10 cm airborne images demonstrate the high accuracy on error detection and show promising results.

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Section: Related Workmentioning

confidence: 99%

Quality evaluation of 3D city building Models with automatic error diagnosis

Michelin

Tierny²,

Tupin³

et al. 2013

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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“…The used DTM has been generated from the correlation DSM using "elastic grid" tools described in (Champion et al, 2010).…”

Section: "La Réunion" Test Areamentioning

confidence: 99%

“…This method is a way to obtain a mask of alarms but also a confidence score related to the recurrence of alarms and to belief given to the different sources of alarms. Besides, as some existing methods work at building level (such as (Rottensteiner, 2007) or (Champion et al, 2010)), alarms could be associated to a building (new, demolished or modified) and a confidence score computed for each building (using the scheme presented above), making it possible to sort alarms from the most to the least plausible.…”

Section: Merge Alarmsmentioning

confidence: 99%

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Change Detection in a Topographic Building Database Using Submetric Satellite Images

Bris¹,

Chehata

2013

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:Submetric satellite imagery (Pleiades, GeoEye) offers advantages for map update purposes, e.g. an interesting ground resolution, a good reactivity and the ability to capture wide areas. Experiments on the use of such stereoscopic images for 2D change detection among building objects of GIS topographic database are presented in this paper. Two approaches have been tested. The first one extracts land cover from satellite ortho-images and additional information (correlation DSM-DTM, database) and compares building objects of this classification to those of the database. The second one creates a pseudo-DSM from height information of database building objects combined with a DTM and compares it to a correlation DSM computed from satellite images. Obtained results are quite encouraging even if the correctness rate remains too low for an operational use.

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“…Among the various recently proposed methods, those based on Markov Random Fields [8,24,1], kernels [2,26] and neural networks [22,23] have gained important attention. Focusing on man-made object change detection [4,20] in urban and peri-urban regions, several approaches have been proposed based on very high resolution optical and radar data [19,23,6,20]. However, these change detection techniques assume and require accurately co-registered data in order to perform pixel-by-pixel or region-by-region multi-temporal data fusion, correlation or any change analysis.…”

Section: Introductionmentioning

confidence: 99%

Simultaneous registration and change detection in multitemporal, very high resolution remote sensing data

Vakalopoulou

Kαράτζαλος

Komodakis

et al. 2015

2015 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)

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In order to exploit the currently continuous streams of massive, multi-temporal, high-resolution remote sensing datasets there is an emerging need to address efficiently the image registration and change detection challenges. To this end, in this paper we propose a modular, scalable, metric free single shot change detection/registration method. The approach exploits a decomposed interconnected graphical model formulation where registration similarity constraints are relaxed in the presence of change detection. The deformation space is discretized, while efficient linear programming and duality principles are used to optimize a joint solution space where local consistency is imposed on the deformation and the detection space. Promising results on large scale experiments demonstrate the extreme potentials of our method.

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2D building change detection from high resolution satelliteimagery: A two-step hierarchical method based on 3D invariant primitives

Cited by 43 publications

References 15 publications

Quality evaluation of 3D city building Models with automatic error diagnosis

Quality evaluation of 3D city building Models with automatic error diagnosis

Change Detection in a Topographic Building Database Using Submetric Satellite Images

Simultaneous registration and change detection in multitemporal, very high resolution remote sensing data

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