Large Field and Binocular Vision Calibration Algorithm Based on Position and Orientation Constraints

Zhang, Chao; Cheng, 韩成 Han; Huamin, 杨华民 Yang; Fan, 杨帆 Yang

doi:10.3788/aos201636.0115003

Cited by 1 publication

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“…Multi-view dense matching uses EPnP algorithm [44][45][46] to establish the mapping relationship between multi-view images pose which describes images position on models and model surface patches. Generally, texture mapping is carried out automatically after multi-view images matching based on the optimal geometric visual angle [30].…”

Section: Semi-automatic Texture Selection Mappingmentioning

confidence: 99%

A Texture Selection Approach for Cultural Artifact 3D Reconstruction Considering Both Geometry and Radiation Quality

Wang

et al. 2020

Remote Sensing

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3D reconstruction of culture artifacts has great potential in digital heritage documentation and protection. Choosing the proper images for texture mapping from multi-view images is a major challenge for high precision and high quality 3D reconstruction of culture artifacts. In this study, a texture selection approach, considering both the geometry and radiation quality for 3D reconstruction of cultural artifacts while using multi-view dense matching is proposed. First, a Markov random field (MRF) method is presented to select images from the best angle of view among texture image sets. Then, an image radiation quality evaluation model is proposed in the virtue of a multiscale Tenengrad definition and brightness detection to eliminate fuzzy and overexposed textures. Finally, the selected textures are mapped to the 3D model under the mapping parameters of the multi-view dense matching and a semi-automatic texture mapping is executed on the 3DMax MudBox platform. Experimental results with two typical cultural artifacts data sets（bronze wares and porcelain）show that the proposed method can reduce abnormal exposure or fuzzy images to yield high quality 3D model of cultural artifacts.

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Section: Semi-automatic Texture Selection Mappingmentioning

confidence: 99%

A Texture Selection Approach for Cultural Artifact 3D Reconstruction Considering Both Geometry and Radiation Quality

Wang

et al. 2020

Remote Sensing

View full text Add to dashboard Cite

show abstract

Large Field and Binocular Vision Calibration Algorithm Based on Position and Orientation Constraints

Cited by 1 publication

References 0 publications

A Texture Selection Approach for Cultural Artifact 3D Reconstruction Considering Both Geometry and Radiation Quality

A Texture Selection Approach for Cultural Artifact 3D Reconstruction Considering Both Geometry and Radiation Quality

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