Acta Geodaetica et Cartographica Sinica ›› 2020, Vol. 49 ›› Issue (1): 92-107.doi: 10.11947/j.AGCS.2020.20180468

• Photogrammetry and Remote Sensing • Previous Articles     Next Articles

Fast visibility detection without specifying the user-defined biases in multi-view texture mapping

HUANG Xiangxiang, ZHU Quansheng, JIANG Wanshou   

  1. State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China
  • Received:2018-10-12 Revised:2019-08-02 Published:2020-01-16
  • Supported by:
    China Southern Power Grid Technology Project(No. GDKJQQ20161187)

Abstract: The Z-buffer and ray-tracing algorithms are the two popular approaches used in visibility handling for multi-view based texture mapping. However, the accuracies of the two algorithms are limited by the user-defined biases. We propose a solution in which no biases are specified. First, a shader-based rendering is designed according to the projection parameter of oblique photogrammetry to generate each view's initial visibility map (IVM). The fully occluded primitives will be excluded by the depth test of graphics pipeline.Second, projection coverage refinement (PCR) is given to the visible primitives in IVM based on vector rasterization criterion and pixel depth. Last, lazy projection (LP) and iterative vertex-edge sampling (IVES) are proposed to distinguish the partially visible and fully visible primitives. We use two datasets to prove our method's validity. The experimental results show that our method has a better performance than the mainstream algorithm.

Key words: visibility computation, occlusion detection, multiview-based texture reconstruction, oblique photogrammetry, computer graphics pipeline

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