Reconstructing curved surfaces from specular reflection patterns using spline surface fitting of normals

Halstead, Mark A.; Barsky, Brain A.; Klein, Stanley A.; Mandell, Robert B.

doi:10.1145/237170.237272

Cited by 68 publications

(51 citation statements)

References 22 publications

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“…Modeling of specular or shiny surfaces is an important application in inspection of industrial parts, especially in the car manufacturing industry (control of wind shields and bodywork) but also in the control of optical lenses or mirrors, glasses of watches etc. Vision-based reconstruction of specular surfaces is usually based on acquiring images of known patterns or light sources, reflected in the surface to be reconstructed [3,4,6,7,11,14].…”

Section: Introductionmentioning

confidence: 99%

How to Compute the Pose of an Object Without a Direct View?

Sturm

Bonfort

2006

Computer Vision – ACCV 2006

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Abstract. We consider the task of computing the pose of an object relative to a camera, for the case where the camera has no direct view of the object. This problem was encountered in work on vision-based inspection of specular or shiny surfaces, that is often based on analyzing images of calibration grids or other objects, reflected in such a surface. A natural setup consists thus of a camera and a calibration grid, put side-by-side, i.e. without the camera having a direct view of the grid. A straightforward idea for computing the pose is to place planar mirrors such that the camera sees the calibration grid's reflection. In this paper, we consider this idea, describe geometrical properties of the setup and propose a practical algorithm for the pose computation.

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Section: Introductionmentioning

confidence: 99%

How to Compute the Pose of an Object Without a Direct View?

Sturm

Bonfort

2006

Computer Vision – ACCV 2006

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“…Halstead et al, in [6], fit a spline surface to a set of normals, iteratively refining the result. Their method requires an initial seed point on the specular surface, and was applied to the sub-micronic reconstruction of the human cornea.…”

Section: Previous Workmentioning

confidence: 99%

General Specular Surface Triangulation

Bonfort

Sturm

Gargallo

2006

Computer Vision – ACCV 2006

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Abstract. We present a method for the reconstruction of a specular surface, using a single camera viewpoint and the reflection of a planar target placed at two different positions. Contrarily to most specular surface reconstruction algorithms, our method makes no assumption on the regularity or continuity of the specular surface, and outputs a set of 3D points along with corresponding surface normals, all independent from one another. A point on the specular surface can be reconstructed if its corresponding pixel in the image has been matched to its source in both of the target planes. We present original solutions to the problem of dense point matching and planar target pose estimation, along with reconstruction results in real-world scenarii.

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“…Other approaches include those based on mathematical models of specular reflections [10,11], analyzing 3D surface profiles travelled by virtual features (Oren and Nayar [13]), as well as their extensions [14]. Halsead et al [9] proposed a reconstruction algorithm where a surface global model is fitted to a set of normals obtained by imaging a pattern of light reflected by specular surface. Their results were applied to interactive visualization of the cornea.…”

Section: Previous Work and Paper Organizationmentioning

confidence: 99%

Recovering Local Shape of a Mirror Surface from Reflection of a Regular Grid

Savarese

Chen

Perona

2004

Lecture Notes in Computer Science

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Abstract. We present a new technique to recover the shape of an unknown smooth specular surface from a single image. A calibrated camera faces a specular surface reflecting a calibrated scene (for instance a checkerboard or grid pattern). The mapping from the scene pattern to its reflected distorted image in the camera changes the local geometrical structure of the scene pattern. We show that if measurements of both local orientation and scale of the distorted scene in the image plane are available, this mapping can be inverted. Specifically, we prove that surface position and shape up to third order can be derived as a function of such local measurements when two orientations are available at the same point (e.g. a corner). Our results generalize previous work [1,2] where the mirror surface geometry was recovered only up to first order from at least three intersecting lines. We validate our theoretical results with both numerical simulations and experiments with real surfaces.

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Reconstructing curved surfaces from specular reflection patterns using spline surface fitting of normals

Cited by 68 publications

References 22 publications

How to Compute the Pose of an Object Without a Direct View?

How to Compute the Pose of an Object Without a Direct View?

General Specular Surface Triangulation

Recovering Local Shape of a Mirror Surface from Reflection of a Regular Grid

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