A Simple Shadow Based Method for Camera Calibration
ICIAR '08 Proceedings of the 5th international conference on Image Analysis and Recognition
Estimating Geo-temporal Location of Stationary Cameras Using Shadow Trajectories
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part I
Shape Reconstruction and Camera Self-Calibration Using Cast Shadows and Scene Geometries
International Journal of Computer Vision
Qualitative robot localisation using information from cast shadows
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Shape reconstruction from cast shadows using coplanarities and metric constraints
ACCV'07 Proceedings of the 8th Asian conference on Computer vision - Volume Part II
Camera calibration and geo-location estimation from two shadow trajectories
Computer Vision and Image Understanding
GPS coordinates estimation and camera calibration from solar shadows
Computer Vision and Image Understanding
Reasoning about shadows in a mobile robot environment
Applied Intelligence
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This paper presents a method for capturing and computing 3D parallax. 3D parallax, as used here, refers to vertical offset from the ground plane, height. The method is based on analyzing shadows of vertical poles (e.g., a tall building's contour) that sweep the object. Unlike existing beam-scanning approaches, such as shadow or structured light, that recover the distance of a point from the camera, our approach measures the height from the ground plane directly. Previous methods compute the distance from the camera using triangulation between rays outgoing from the light-source and the camera. Such a triangulation is difficult when the objects are far from the camera, and requires accurate knowledge of the light source position. In contrast, our approach intersects two (unknown) planes generated separately by two casting objects. This omits the need to precompute the location of the light source. Furthermore, it allows a moving light source to be used. The proposed setup is particularly useful when the camera cannot directly face the scene or when the object is far away from the camera. A good example is an urban scene captured by a single webcam.