Auto-selection of airborne oblique images for automatic façade texture mapping

Jiann-Yeou Rau, Chan Yi Chu, Liang Chien Chen, Chieh Tsung Chen, Hsu Chen Hsu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Geospatial applications based on photo-realistic building model are getting popular in the field of 3D GIS. Conventionally, the vertical imaging systems are designed for topographic mapping. Thus, it is improper for the extraction of good quality façade texture. On the other hand, for close-range photography, the occlusion and camera orientation problems will introduce not only texture quality issue but also cost-effective problem. The purpose of this paper aims on automatic selection of airborne oblique imagery for facade texture mapping provided that a large quantity of airborne oblique images with exterior and interior orientation parameters, lens distortion parameters and 3D polyhedral building models are existed. In this research, the airborne oblique images were taken from the helicopter with 30 degrees off-nadir angle and a flying height of 650 meters result in 13∼18cm ground sampling distance. Considering a large quantity of oblique images and 3D building models existed in a project, from the automation and efficiency point of view an efficient auto-selection algorithm is necessary. In the paper, many criteria were designed for the filtering of not visible images and for the selection of the best quality image without occlusion from other buildings. At first, for each façade, a visibility analysis is performed for all oblique images. It includes the visibility analysis of target façade within the imaging field-of-view and visible by the image. In order to avoid occlusion from other buildings, a filtering technique base on bounding sphere and bounding circle was developed. Finally, the average ground sampling distance and incident angle were considered for the selection of image with best quality. Experimental results depict that the proposed method can select the best qualified image without occlusion efficiently.

Original languageEnglish
Title of host publication29th Asian Conference on Remote Sensing 2008, ACRS 2008
Pages537-543
Number of pages7
Publication statusPublished - 2008 Dec 1
Event29th Asian Conference on Remote Sensing 2008, ACRS 2008 - Colombo, Sri Lanka
Duration: 2008 Nov 102008 Nov 14

Publication series

Name29th Asian Conference on Remote Sensing 2008, ACRS 2008
Volume1

Other

Other29th Asian Conference on Remote Sensing 2008, ACRS 2008
CountrySri Lanka
CityColombo
Period08-11-1008-11-14

Fingerprint

Textures
Visibility
Sampling
Facades
Photography
Helicopters
Imaging systems
Geographic information systems
Image quality
Lenses
Automation
Cameras
Imaging techniques
Costs

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications

Cite this

Rau, J-Y., Chu, C. Y., Chen, L. C., Chen, C. T., & Hsu, H. C. (2008). Auto-selection of airborne oblique images for automatic façade texture mapping. In 29th Asian Conference on Remote Sensing 2008, ACRS 2008 (pp. 537-543). (29th Asian Conference on Remote Sensing 2008, ACRS 2008; Vol. 1).
Rau, Jiann-Yeou ; Chu, Chan Yi ; Chen, Liang Chien ; Chen, Chieh Tsung ; Hsu, Hsu Chen. / Auto-selection of airborne oblique images for automatic façade texture mapping. 29th Asian Conference on Remote Sensing 2008, ACRS 2008. 2008. pp. 537-543 (29th Asian Conference on Remote Sensing 2008, ACRS 2008).
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abstract = "Geospatial applications based on photo-realistic building model are getting popular in the field of 3D GIS. Conventionally, the vertical imaging systems are designed for topographic mapping. Thus, it is improper for the extraction of good quality fa{\cc}ade texture. On the other hand, for close-range photography, the occlusion and camera orientation problems will introduce not only texture quality issue but also cost-effective problem. The purpose of this paper aims on automatic selection of airborne oblique imagery for facade texture mapping provided that a large quantity of airborne oblique images with exterior and interior orientation parameters, lens distortion parameters and 3D polyhedral building models are existed. In this research, the airborne oblique images were taken from the helicopter with 30 degrees off-nadir angle and a flying height of 650 meters result in 13∼18cm ground sampling distance. Considering a large quantity of oblique images and 3D building models existed in a project, from the automation and efficiency point of view an efficient auto-selection algorithm is necessary. In the paper, many criteria were designed for the filtering of not visible images and for the selection of the best quality image without occlusion from other buildings. At first, for each fa{\cc}ade, a visibility analysis is performed for all oblique images. It includes the visibility analysis of target fa{\cc}ade within the imaging field-of-view and visible by the image. In order to avoid occlusion from other buildings, a filtering technique base on bounding sphere and bounding circle was developed. Finally, the average ground sampling distance and incident angle were considered for the selection of image with best quality. Experimental results depict that the proposed method can select the best qualified image without occlusion efficiently.",
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Rau, J-Y, Chu, CY, Chen, LC, Chen, CT & Hsu, HC 2008, Auto-selection of airborne oblique images for automatic façade texture mapping. in 29th Asian Conference on Remote Sensing 2008, ACRS 2008. 29th Asian Conference on Remote Sensing 2008, ACRS 2008, vol. 1, pp. 537-543, 29th Asian Conference on Remote Sensing 2008, ACRS 2008, Colombo, Sri Lanka, 08-11-10.

Auto-selection of airborne oblique images for automatic façade texture mapping. / Rau, Jiann-Yeou; Chu, Chan Yi; Chen, Liang Chien; Chen, Chieh Tsung; Hsu, Hsu Chen.

29th Asian Conference on Remote Sensing 2008, ACRS 2008. 2008. p. 537-543 (29th Asian Conference on Remote Sensing 2008, ACRS 2008; Vol. 1).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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AB - Geospatial applications based on photo-realistic building model are getting popular in the field of 3D GIS. Conventionally, the vertical imaging systems are designed for topographic mapping. Thus, it is improper for the extraction of good quality façade texture. On the other hand, for close-range photography, the occlusion and camera orientation problems will introduce not only texture quality issue but also cost-effective problem. The purpose of this paper aims on automatic selection of airborne oblique imagery for facade texture mapping provided that a large quantity of airborne oblique images with exterior and interior orientation parameters, lens distortion parameters and 3D polyhedral building models are existed. In this research, the airborne oblique images were taken from the helicopter with 30 degrees off-nadir angle and a flying height of 650 meters result in 13∼18cm ground sampling distance. Considering a large quantity of oblique images and 3D building models existed in a project, from the automation and efficiency point of view an efficient auto-selection algorithm is necessary. In the paper, many criteria were designed for the filtering of not visible images and for the selection of the best quality image without occlusion from other buildings. At first, for each façade, a visibility analysis is performed for all oblique images. It includes the visibility analysis of target façade within the imaging field-of-view and visible by the image. In order to avoid occlusion from other buildings, a filtering technique base on bounding sphere and bounding circle was developed. Finally, the average ground sampling distance and incident angle were considered for the selection of image with best quality. Experimental results depict that the proposed method can select the best qualified image without occlusion efficiently.

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M3 - Conference contribution

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Rau J-Y, Chu CY, Chen LC, Chen CT, Hsu HC. Auto-selection of airborne oblique images for automatic façade texture mapping. In 29th Asian Conference on Remote Sensing 2008, ACRS 2008. 2008. p. 537-543. (29th Asian Conference on Remote Sensing 2008, ACRS 2008).