测绘通报 ›› 2024, Vol. 0 ›› Issue (4): 140-144.doi: 10.13474/j.cnki.11-2246.2024.0424

• 技术交流 • 上一篇    

一种基于光学几何和建筑物特征识别的倾斜摄影冗余航片筛选方法

陈广亮1, 谢运广1, 刘禹麒1, 蔡岳臻2, 陈定安2   

  1. 1. 广州蓝图地理信息技术有限公司, 广东 广州 510650;
    2. 中山大学地理科学与规划学院, 广东 广州 510275
  • 收稿日期:2023-09-15 发布日期:2024-04-29
  • 通讯作者: 谢运广。E-mail:93763540@qq.com
  • 作者简介:陈广亮(1990—),男,硕士,工程师,研究方向为实景三维、自然资源调查等。E-mail:1210920114@qq.com
  • 基金资助:
    中山大学横向结题项目续研预研经费(37000-14090113);广州蓝图地理信息技术有限公司科研项目(2021RD8)

A screening method of redundant aerial photographs for oblique photogrammetry based on optical geometry and building feature recognition

CHEN Guangliang1, XIE Yunguang1, LIU Yuqi1, CAI Yuezhen2, CHEN Dingan2   

  1. 1. Guangzhou Lantu Geographic Information Co., Ltd., Guangzhou 510650, China;
    2. School of Geometry and Planning, Sun Yat-sen University, Guangzhou 510275, China
  • Received:2023-09-15 Published:2024-04-29

摘要: 为满足测区覆盖需要,测绘业界近年流行采用多目镜相机(以五目为主)进行倾斜摄影测量,从而使航测时间显著减少。但与此同时,五目相机会产生大量未覆盖测区范围的冗余航片,在具有不规则形状的测区更为严重,导致大量冗余航片参与三维重建, 耗费计算成本。对此,本文提出了一种基于光学几何和建筑物特征识别的倾斜摄影冗余航片筛选方法,首先通过航片的内外方位函数计算航片在地表的投影范围,同时结合建筑物特征识别保留测区边缘的有效航片以保证建模质量。试验表明,该方法能够在复杂测区内判别约占整体照片量约70%的冗余航片,且在加入建筑物特征后可以减少三维模型失真、拉花等现象,验证了该方法的准确性和有效性。

关键词: 倾斜摄影, 航片筛选, 影像范围计算, 图像特征识别

Abstract: Integrated multiple lens cameras have been adopted for aerial photogrammetry in the industries in recent years thanks to its high data-acquisition efficiency. However, the cameras yield redundant photos for non-target areas which causes extra computation power. This issue becomes serious when the shape of the target area gets complicated. In this paper, we propose a novel screening method for the redundant aerial photos based on optical geometry and building recognition algorithms. The method first project the photos onto target area, and the overlaps are estimated. Combining the building recognition results with the estimated overlap ratios, the redundant photos can be identified and removed. The results suggest that the proposed method is able to reduce 70% of the captured photos but keep almost the same accuracy for reconstruction of the target area.

Key words: oblique photogrammetry, redundant photo removal, overlapping area estimation, pattern and feature recognition

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