无物方信息的未检校近景影像的方位元素估计

Orientation Parameters Estimation for Uncalibrated Close range Image Sequences Without Scene Information

摘要:

无物方控制信息的未检校立体影像序列只能实现度量重建，而实现度量重建必须恢复内外方位元素，利用层次重建方法，根据三张以上同名像点，用迭代分解算法恢复投影矩阵和结构，然后采用基于绝对二次曲面的自检校方法恢复相机的内方位元素，并进一步得到外方位元素.此方法可以在不需要物方控制的条件下得到统一模型，若有物方控制即可通过绝对定向获取物方坐标,可用于低精度的三维测量，也可作为高精度光束法平差的初值.

Abstract:

Metric reconstruction is the highest level reconstruction obtained from uncalibrated image sequences without any scene information, which needs recovering interior and exterior parameters. According to the stratified reconstruction approaches in computer vision, projective matrix and structure are recovered from the correspondences of more than three views through iterative singular value decomposition algorithm, then interior parameters can be estimated through the absolute quadric self calibration method, then exterior parameters are recovered subsequently. With this approach, free models are available without any scene information, Euclidean reconstruction can be realized through absolute orientation when sufficient scene controls are available. The orientation results can be used in low accuracy 3 dimensional measurement or as the initial values for high accuracy bundle adjustment.