Omni-directional 3D Measurement by Hyperbolic Mirror Cameras and Pattern Projection

Ukida, Hiroyuki; Yamato, Naofumi; Tanimoto, Yasuhiro; Sano, Tetsuya; Yamamoto, Hideki

doi:10.1109/imtc.2008.4547062

Cited by 13 publications

(10 citation statements)

References 1 publication

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“…The relation between the camera coordinates (X, Y, Z) of a space point P and the image coordinates (u, v) of its corresponding projection pixel p may be described [22] as…”

Section: Overview Of Proposed Systemmentioning

confidence: 99%

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A Two-Omni-Camera Stereo Vision System With an Automatic Adaptation Capability to Any System Setup for 3-D Vision Applications

Shih

Tsai

2013

IEEE Trans. Circuits Syst. Video Technol.

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A stereo vision system using two omni-cameras for 3-D vision applications is proposed, which has an automatic adaptation capability to any system setup before 3-D data computation is conducted. The adaptation, which yields the orientations and distance of the two omni-cameras, is accomplished by detecting and analyzing the horizontal lines appearing in the omni-images acquired with the cameras and a person standing in front of the cameras. Properties of line features in environments are utilized for detecting more precisely the horizontal lines that appear as conic sections in omni-images. The detection work is accomplished through the use of carefully chosen parameters and a refined Hough transform technique. The detected horizontal lines are utilized to compute the cameras' orientations and distance from which the 3-D data of space points are derived analytically. Compared with a traditional system using a pair of projective cameras with nonadjustable camera orientations and distance, the proposed system has the advantages of offering more flexibility in camera setups, better usability in wide areas, higher precision in computed 3-D data, and more convenience for nontechnical users. Good experimental results show the feasibility of the proposed system. Index Terms-3-D vision applications, automatic adaptation, omni-camera, omni-image, stereo vision, system setup.

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“…The relation between the camera coordinates (X, Y, Z) of a space point P and the image coordinates (u, v) of its corresponding projection pixel p may be described [22] as…”

Section: Overview Of Proposed Systemmentioning

confidence: 99%

“…which, when combined with (20), (21), (22), and (23), leads to the following estimation result for use as the desired 3-D data of space point P:…”

Section: B Calculating 3-d Data Of Space Feature Pointsmentioning

confidence: 99%

A Two-Omni-Camera Stereo Vision System With an Automatic Adaptation Capability to Any System Setup for 3-D Vision Applications

Shih

Tsai

2013

IEEE Trans. Circuits Syst. Video Technol.

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“…According to [8,9], the relation between the camera coordinates (X, Y, Z) of a space point P and the image coordinates (u, v) of its corresponding image point p may be described by the following equalities, where D and E are two space angles as illustrated in Fig. 4:…”

Section: (A) Task a Circular Shape Detectionmentioning

confidence: 99%

An omni-vision based localization method for automatic helicopter landing assistance on standard helipads

Tsai

2010

2010 the 2nd International Conference on Computer and Automation Engineering (ICCAE)

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An omni-vision-based localization method for automatic helicopter landing assistance on a helipad with a circled H-shape is proposed. The landing process includes two stages: approaching and alignment. Three types of image features, circle, line, and point, are used to derive skillfully analytic equations for computing the helicopter height, distance, and orientation with respect to the landing site. Experimental results with good location estimation accuracy are also shown. †

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“…Four laser diodes with diffractive of elements (DOE) are used to shoot regular dot matrix patterns to obtain a 3D reconstruction [21]. Similarly, multiple sets of projectors have been used to shoot different encoded patterns onto an ambient scene [23], and then, a catadioptric camera is used to capture the distorted patterns to greatly improve the spatial resolution of the measured point cloud. However, for the above systems, some blind spots still exist when local region reconstruction is performed.…”

Section: Introductionmentioning

confidence: 99%

3D multi-directional sensor with pyramid mirror and structured light

Wang

Yao

et al. 2017

Optics and Lasers in Engineering

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Structured-light-based 3D multi-directional sensors are widely used due to their flexible field of view (FOV), which is a significant benefit. Nevertheless, existing 3D multi-directional sensors based on linear lasers are only capable of measuring a slice of a 3D scene at low resolution. In addition, other 3D multi-directional sensors are capable of measuring 3D scenes by shooting 2D structured light patterns in different directions through curved mirrors. However, the projected and captured structured light patterns are blurred due to the optical aberration property of curved mirrors, resulting in inaccurate 3D reconstruction. This paper proposes a 3D, high-resolution, high-accuracy, real-time multi-directional sensor that utilizes pyramid mirrors to decompose the FOVs into different directions and reduce the optical aberration phenomenon. The mathematical model of the 3D sensor is presented, and the FOV is analyzed. A dual-frequency phase-shifting fringe pattern is used for 3D reconstruction in real time. Moreover, the sensor is calibrated using a planar circle calibration gauge and the Householder reflection constraint. Finally, the experimental results demonstrate that the measurement error of the 3D multi-directional sensor is less than 1mm and 0.03rad, thus verifying the method's feasibility.

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Omni-directional 3D Measurement by Hyperbolic Mirror Cameras and Pattern Projection

Cited by 13 publications

References 1 publication

A Two-Omni-Camera Stereo Vision System With an Automatic Adaptation Capability to Any System Setup for 3-D Vision Applications

A Two-Omni-Camera Stereo Vision System With an Automatic Adaptation Capability to Any System Setup for 3-D Vision Applications

An omni-vision based localization method for automatic helicopter landing assistance on standard helipads

3D multi-directional sensor with pyramid mirror and structured light

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