넓은 시야각을 갖는 전방향(omnidirectional) 카메라 시스템은 적은 수의 영상으로도 주변 장면에 대해 많은 정보를 취득할 수 있는 장점으로 감시, 3차원 해석 등의 분야에 널리 응용되고 있다. 본 논문에서는 어안(fisheye) 렌즈를 이용한 전방향 카메라로 입력된 영상으로부터 카메라의 이동 및 회전 파라미터를 자동으로 추정하는 새로운 자동보정 알고리즘이 제안되었다. 먼저, 카메라 위치를 임의의 각 도로 변환하여 얻어진 영상을 이용해 일차 매개변수로 표현된 카메라의 사영(projection)모델을 추정한다. 그리고 이후 다양하게 변환되는 카메라의 위치에 따라 에센셜(essential) 행렬을 구하며, 이 과정에서 대상 영상으로부터 적합한 인라이어(inlier) 집합을 구하기 위해 특징점이 영역 내에 분포 정도를 반영하는 표준편차(standard deviation)를 정량적(quantitative) 기준으로 이용한다. 다양한 실험을 통해 제안된 알고리즘이 전방향 카메라의 사영 모델과 회전, 이동 등의 변환 파라미터를 정확하게 추정함을 확인하였다.

This paper presents a new sensor system. CALOS, for motion estimation and 3D reconstruction. The 2D laser sensor provides accurate depth information of a plane, not the whole 3D structure. On the contrary, the CCD cameras provide the projected image of whole 3D scene, not the depth of the scene. To overcome the limitations, we combine these two types of sensors, the laser sensor and the CCD cameras. We develop a motion estimation scheme appropriate for this sensor system.In the proposed scheme, the motion between two frames is estimated by using three points among the scan data and their corresponding image points, and refined by non-linear optimization. We validate the accuracy of the proposed method by 3D reconstruction using real images. The results show that the proposed system can be a practical solution for motion estimation as well as for 3D reconstruction.

The problem of establishing the servo system to reach the desired location keeping all features in the field of view and following a straight line is considered. In addition, robustness of camera calibration parameters is considered in this paper. The proposed approach is based on switching from position-based visual servoing (PBVS) to image-based visual servoing (IBVS) and allows the camera path to follow a straight line. To achieve the objective, a pose estimation method is required; the camera's target pose is estimated from the obtained images without the knowledge of the object. A switched control law moves the camera equipped to a robot end-effector near the desired location following a straight line in Cartesian space and then positions it to the desired pose with robustness to camera calibration error. Finally simulation results show the feasibility of the proposed visual servoing technique.

Camera arrangement for depth and image correspondence is very important to the computer vision. Two conventional comera arrangements for stereo computer vision are lateral model and axial motion model. In this paper, using the axial motion stereo camera model, the algorithm for camera focal length measurement and the surface smoothness with the radiance-irradiance is proposed fro 3-dimensional image correspondence on stereo computer vision. By adapting the above algorithm, camera focal length can be measured precisely and the resolution of 3-dimensional image correspondence has been improved comparing to that of the axial motion model without the radiance-irradiance relation.