Vol.34, pp. 351-359
In this paper, we present a new algorithm for the calibration of a camera and the recovery of 3D scene structure up to a
scale from image sequences using known angles between lines in the scene. The proposed method computes the intrinsic
parameters of camera using the invariance of angles under the similarity transformation. Speci"cally, we recover the
matrix that is the homography between the projective structure and the Euclidean structure using angles. Since this
matrix is a unique one in the given set of image sequences, we can easily deal with the problem of varying intrinsic
parameters of the camera. Experimental results on the synthetic and real images demonstrate the feasibility of the
proposed algorithm.
In this paper, we present a new algorithm for the calibration of a camera and the recovery of 3D scene structure up to a
scale from image sequences using known angles between lines in the scene. The proposed method computes the intrinsic
parameters of camera using the invariance of angles under the similarity transformation. Speci"cally, we recover the
matrix that is the homography between the projective structure and the Euclidean structure using angles. Since this
matrix is a unique one in the given set of image sequences, we can easily deal with the problem of varying intrinsic
parameters of the camera. Experimental results on the synthetic and real images demonstrate the feasibility of the
proposed algorithm.