3D photography on your desk

Bouguet, J.-Y.; Perona, Pietro

doi:10.1109/iccv.1998.710699

Cited by 121 publications

(75 citation statements)

References 10 publications

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“…From the calibration process, a plane of z = 0 is also defined on the calibration board, onto which the occluding object cast shadows. 2 The question of how to select image pixels to obtain a solution set for unknown radiance values seems to be leading to an interesting research topic. For instance, a similar discussion on this subject can be found in [10].…”

Section: Known Reflectance Properties: Non-lambertian Modelmentioning

confidence: 99%

“…Shadows in a real scene are caused by the occlusion of incoming lights as illustrated in Figure 1, and thus shadows contain various pieces of information about the illumination of the scene. Nevertheless, in the past, shadows have been used for determining the 3D shapes and orientations of an object which cast shadows onto the scene [2,11,14,19], while very few studies have focused on the the illuminant information which shadows could provide.…”

Section: Introductionmentioning

confidence: 99%

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Illumination Distribution from Shadows

Sato¹,

Sato²,

Ikeuchi³

2001

Modeling From Reality

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Section: Known Reflectance Properties: Non-lambertian Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Illumination Distribution from Shadows

Sato¹,

Sato²,

Ikeuchi³

2001

Modeling From Reality

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“…In these methods, the laser planes are calibrated by using calibration objects such as fixed frames, markers, or known planes, then the points on the laser (shadow) planes are reconstructed using triangulations. Bouguet et al proposed a method in which the scene is scanned by shadows of a straight edge to reconstruct the scene [2]. Their technique requires calibration of camera parameters, a light source position, and a reference plane.…”

Section: Related Studiesmentioning

confidence: 99%

Geometrical constraint based 3D reconstruction using implicit coplanarities

Furukawa¹,

Kawasaki²

2007

Procedings of the British Machine Vision Conference 2007

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Coplanarity is a relationship of a set of points that exist on a single plane. Coplanarities can be easily observed in a scene with planer surfaces, and these types of coplanarities have been widely used for 3D reconstructions based on geometrical constraints. Other types of coplanarities that can be observed from images are those observed as cross sections of planes and scenes; for example, points lit by a line laser, or boundary points of a shadow of a straight edge. Although these types of coplanarities have been implicitly used in variations of light sectioning methods, they have not been used in an unified manner with the former types. In this paper, we describe a new 3D reconstruction method based on coplanarities and other geometrical constraints. In particular, we make use of the above two types of coplanarities in an unified manner. This enables us to reconstruct 3D scenes scanned using line lasers or shadows of straight edges observed by a partially-calibrated single camera utilizing geometrical relationships between the planes in the scenes and the planes of line lasers or the planes of shadow boundaries.

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“…The use of shadow trajectory of a gnomon to measure time in a sundial is reported as early as 1500 BC by Egyptians, which surprisingly requires sophisticated astronomical knowledge [1,2,3]. Shadows have been used in multiple-view geometry in the past to provide information about the shape and the 3-D structure of the scene [4,5], or to recover camera intrinsic and extrinsic parameters [6,7]. Determining the GPS coordinates and the date of the year from shadows in images is a new concept that we introduce in this paper.…”

Section: Introductionmentioning

confidence: 99%

Estimating Geo-temporal Location of Stationary Cameras Using Shadow Trajectories

Junejo

Foroosh

2008

Lecture Notes in Computer Science

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Abstract. Using only shadow trajectories of stationary objects in a scene, we demonstrate that using a set of six or more photographs are sufficient to accurately calibrate the camera. Moreover, we present a novel application where, using only three points from the shadow trajectory of the objects, one can accurately determine the geo-location of the camera, up to a longitude ambiguity, and also the date of image acquisition without using any GPS or other special instruments. We refer to this as "geo-temporal localization". We consider possible cases where ambiguities can be removed if additional information is available. Our method does not require any knowledge of the date or the time when the pictures are taken, and geo-temporal information is recovered directly from the images. We demonstrate the accuracy of our technique for both steps of calibration and geo-temporal localization using synthetic and real data.

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3D photography on your desk

Cited by 121 publications

References 10 publications

Illumination Distribution from Shadows

Illumination Distribution from Shadows

Geometrical constraint based 3D reconstruction using implicit coplanarities

Estimating Geo-temporal Location of Stationary Cameras Using Shadow Trajectories

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