A Shape Measurement Method Based on Uncalibrated Image Sequence
基于未标定序列图的形貌测量方法

In this paper a novel reconstruction algorithm for extracting the three-dimensional coordinates of feature points in a structure and the movement matrix of video camera at the same time is proposed to realize three-dimensional shape measurement based on uncalibrated sequence of an arbitrary number of images. The scaled projection matrix was firstly discussed and expressed by homogenous coordinates of spatial points. The definition of projection ratio was derived from the matrix. Taking advantage of the projections of 3D points onto an image sequence, iterative projective depths were calculated, the depth data with higher accuracy than the binocular vision were obtained. The projective solution was then converted to a Euclidean one by enforcing metric constraints. A factorization-based normalization algorithm was presented to generate the Euclidean reconstruction and the intrinsic parameters. Results of reconstruction of regular marks on a non-planar surface by this method are presented in this paper. Three dimensional shape data were analyzed with absolute errors under 0.16mm.