Trinocular active range-sensing

Blake, A.; McCowen, D.; Lo, H. R.; Lindsey, Peter

doi:10.1109/34.211467

Cited by 40 publications

(8 citation statements)

References 15 publications

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“…5 To avoid difficulty in identification of the corresponding feature points in two images, a trinocular-matching algorithm has been proposed, in which a third camera is employed to overcome the problems inherent in binocular stereomatching. 6 Normally, the feature points, such as the edges or corners of the object at which the image intensity varies rapidly, are identified to match the images taken by multiple cameras that are placed at different positions and to calculate the 3-D coordinates. However, in an ambient lighting environment, there are three major obstacles that cause problems in securing feature point matching.…”

Section: Introductionmentioning

confidence: 99%

Miniaturized three-dimensional endoscopic imaging system based on active stereovision

Chan¹,

Lin²,

Zhou³

et al. 2003

Appl. Opt.

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A miniaturized three-dimensional endoscopic imaging system is presented. The system consists of two imaging in channels that can be used to obtain an image from an object of interest and to project as tructured light onto the imaged object to measure the surface topology. The structured light was generated with a collimated monochromatic light source and a holographic binary phase grating. The imaging and projection channels were calibrated by use of a modified pinhole camera. The surface profile was extracted by use of triangulation between the projected feature points and the two channel ofthe endoscope. The imaging system was evaluated in three-dimensional measurements of several objects with known geometries. The results show that surface profiles of the objects with different surfaces and dimensions can be obtained at high accuracy. The in vivo measurements at tissue sites of human skin and an oral cavity demonstrated the potential of the technique for clinical applications.

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Section: Introductionmentioning

confidence: 99%

Miniaturized three-dimensional endoscopic imaging system based on active stereovision

Chan¹,

Lin²,

Zhou³

et al. 2003

Appl. Opt.

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“…The camera was calibrated by using the techniques presented by [5] and [15]. The projected dot pattern was rotated against the horizontal line to achieve a near-degenerate epipolar alignment [1].…”

Section: Structured Light Technique To Acquire Distance Pointsmentioning

confidence: 99%

Head Detection and Localization from Sparse 3D Data

Clabian¹,

Rötzer²,

Bischof

et al. 2002

Lecture Notes in Computer Science

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Abstract.Head detection is an important, but difficult task, if no restrictions such as static illumination, frontal face appearance or uniform background can be assumed. We present a system that is able to perform head detection under very general conditions by employing a 3D measurement system namely a structured light distance measurement. An algorithm of head detection from sparse 3D data (19x19 data points) is developed that reconstructs a 3D surface over the image plane and detects head hypotheses of ellipsoidal shape. We demonstrate that detection and rough localization is possible in up to 90% of the images.

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“…A typical application is that of multiple-camera visioning configurations such as trinocular vision systems. Such systems can be broadly classified as either right triangular [2,4,29,36], parallel [30], surrounding [23], divergent [33], orthogonal [40], or arbitrary [7,16,17]. The first four types are coplanar, while the remainder are non-coplanar.…”

Section: Introductionmentioning

confidence: 98%