A Mobile System Using Lidar and Photogrammetry for Urban Spatial Objects Extraction

Geng, Xuexian; Zhong, Shuncong

doi:10.1109/iciecs.2009.5365334

Cited by 5 publications

(2 citation statements)

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“…The detailed parallax interpolation method based on DPM is described as follows. Firstly, select n points in DPM, which fall into the square centered by the matching point, with the edge length L. Secondly, use the bivariate high-order polynomial defined by the following formula (5) to fit parallax surface, and use selected n points to work out coefficients of polynomial by least squares method. Lastly, input row and column coordinates of matching point to the formula (5), and work out initial horizontal parallax value of this point on right image…”

Section: Confirmation Searching Range Of Homologous Pointmentioning

confidence: 99%

“…In recent years, vehicle-borne mobile mapping systems (VMMS) integrated with multisensors as GPS, INS, laser scanner, and CCD cameras have grown rapidly for quick acquisition of geospatial data [1][2][3][4][5]. The most important subsystem of VMMS is digital photogrammetric system, which can extract geometric information of ground objects efficiently and rapidly, and has been widely used in many fields as surveying and mapping [6,7], 3D modeling [8][9][10] industrial surveying [11], traffic engineering [12], and so forth.…”

Section: Introductionmentioning

confidence: 99%

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Stereo Image Matching for Vehicle-Borne Mobile Mapping System Based on Digital Parallax Model

Sheng

2011

International Journal of Vehicular Technology

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Considering automatic and effective stereo image matching for vehicle-borne mobile mapping system (VMMS), a new stereo image matching algorithm based on digital parallax model (DPM) is proposed in this paper. The new matching propagation strategy is designed in this algorithm, which includes two processes as DPM construction and parallax prediction. With some known matched points, the DPM of stereo image pairs is firstly constructed, and parameters for confirming conjugate epipolar line is also worked out. Then searching range during dense matching can be confirmed under constraints of DPM and epipolar line, which can improve matching speed and accuracy. Furthermore, to improve matching robustness, the computation model of similarity measurement combined with local structure feature and global color feature is designed. The new algorithm is applied to actual stereo images taken by VMMS to verify its validity. Experimental results show that the proposed approach has higher reliability and accuracy.

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Section: Confirmation Searching Range Of Homologous Pointmentioning

confidence: 99%