Euclidean reconstruction by means of an uncalibrated structured light sensor (original) (raw)
Related papers
Uncalibrated reconstruction: an adaptation to structured light vision
Pattern Recognition, 2003
Euclidean reconstruction from two uncalibrated stereoscopic views is achievable from the knowledge of geometrical constraints about the environment. Unfortunately, these constraints may be quite di cult to obtain. In this paper, we propose an approach based on structured lighting, which has the advantage of providing geometrical constraints independent of the scene geometry. Moreover, the use of structured light provides a unique solution to the tricky correspondence problem present in stereovision. The projection matrices are ÿrst computed by using a canonical representation, and a projective reconstruction is performed. Then, several constraints are generated from the image analysis and the projective reconstruction is upgraded into an Euclidean one-as we will demonstrate, it is assumed that the sensor behaviour is a ne without loss of generality so that the constraints generation is simpliÿed. The method provides our sensor with adaptive capabilities and permits to be used in the measurement of moving scenes such as dynamic visual inspection or mobile robot navigation. Experimental results obtained from both simulated and real data are presented.
Uncalibrated vision based on structured light
Proceedings 2001 ICRA. IEEE International Conference on Robotics and Automation (Cat. No.01CH37164)
The recovery of the three-dimensional structure of the environment is a prerequisite for many tasks in mobile robotics. Unfortunately, calibration acts as a brake upon visual adaptation and robotical autonomy. In this paper, we provide tools and constraints based on structured light for a complete and efficient uncalibrated Euclidean reconstruction of the environment. Experimental results achieved both on simulated and real data validate the method. 3 Tools for Uncalibrated Vision This section first recalls the definition of the cross-ratio and its basic formulations. Then, it is described how to use it to perform a test of spatial colinearity and a test of coplanarity only from pixel coordinates .
Towards a real-time 3D shape reconstruction using a structured light system
Pattern Recognition, 2005
This paper deals with 3D shape reconstruction using a structured light system (SLS) which projects a matrix of laser rays onto the scene to be analyzed. The intrinsic problem of such a system is the correspondence problem solving, which in this particular case amounts to matching up the imaged spots and the originating laser rays. In this paper, we propose a method for automatically obtaining configurations of the system (COS) (i.e. the relative positions of the camera, laser projector, and measuring scene) that permit to achieve a direct and unambiguous correspondence. After, we propose a splitting cell algorithm, which efficiently performs a real-time correspondence procedure. Experimental results obtained from both simulated and real data demonstrate that our method provides our SLS with possibilities for real-time applications.
Flexible calibration of structured-light systems projecting point patterns
Computer Vision and Image Understanding, 2013
Structured-light systems (SLSs) are widely used in active stereo vision to perform 3D modelling of a surface of interest. We propose a flexible method to calibrate SLSs projecting point patterns. The method is flexible in two respects. First, the calibration is independent of the number of points and their spatial distribution inside the pattern. Second, no positioning device is required since the projector geometry is determined in the camera coordinate system based on unknown positions of the calibration board. The projector optical center is estimated together with the 3D rays originating from the projector using a numerical optimization procedure. We study the 3D point reconstruction accuracy for two SLSs involving a laser based projector and a pico-projector, respectively, and for three point patterns. We finally illustrate the potential of our active vision system for a medical endoscopy application where a 3D cartography of the inspected organ (a large field of view surface also including image textures) can be reconstructed from a video acquisition using the laser based SLS.
Scaled Euclidean 3D reconstruction based on externally uncalibrated cameras
Proceedings of International Symposium on Computer Vision - ISCV, 1995
Previous work sh,ows that based on five noncoplanar correspondences of two uncalibrated cameras, 3 0 reconstruction can be achieved under projective models, or based on four non-coplanar correspon,dences of two uncalibrated cameras, 3 0 recon.struction, can be achieved m d e r a@ne models, with three unknoiun parameters. In th,is paper, we show that based on four coplanar correspondences of two externally uncalibrated cameras, SD reconstruction can be achieved in Euclidean. space with only one unknown s c a h g parameter. Moreover, the unknown, scale factor is the physical distance from the camera center to the plane formed b y the four points in SD space. If th.is distance is known a priori, then the 3D structure can be conzpletely recovered. Both simulated and real data experimental results show that our reconstruction algorithm works reasonably robustly.
3-D Computer Vision Using Structured Light: Design, Calibration, and Implementation Issues
Advances in Computers, 1996
Structured Light (SL) sensing is a well established m e t h o d o f r ange acquisition for Computer Vision. This chapter provides thorough discussions of design issues, calibration methodologies and implementation schemes for SL sensors. The challenges for SL sensor development are described and a range of approaches are surveyed. A novel SL sensor, PRIME, the PRo�le Imaging ModulE has recently been developed and is used as a design example in the detailed discussions.
Recent progress in structured light in order to solve the correspondence problem in stereovision
Proceedings of International Conference on Robotics and Automation
We present a summary of the most significant techniques, used in the last few years, concerning the coded structured light methods employed to get 3D information. In fact, depth perception is one of the most important subjects in computer vision. Stereovision is an attractive and widely used method, but, rather limited to make 3D surface maps, due to the correspondence problem. The correspondence problem can be improved using a method based on structured light concept, projecting a given pattern on the measuring surfaces, although some relations between the projected pattern and the reflected one must be solved. This relationship can be directly found codifying the projected light, so that, each imaged region of the projected pattern carries the necessary information to solve the correspondence problem. We do not need to mention the numerous advantages that presents an accurate obtention of 3D information for many research subjects, such as: robotics, autonomous navigation, shape analysis, and so on.
1998
We present a survey of the most significant techniques, used in the last few years, concerning the coded structured light methods employed to get 3D information. In fact, depth perception is one of the most important subjects in computer vision. Stereovision is an attractive and widely used method, but, it is rather limited to make 3D surface maps, due to the correspondence problem. The correspondence problem can be improved using a method based on structured light concept, projecting a given pattern on the measuring surfaces. However, some relations between the projected pattern and the reflected one must be solved. This relationship can be directly found codifying the projected light, so that, each imaged region of the projected pattern carries the needed information to solve the correspondence problem.
A Structured-Light Approach for the Reconstruction of Complex Objects
Geoinformatics FCE CTU, 2011
Recently, one of the central issues in the fields of Photogrammetry, Computer Vision, Computer Graphics and Image Processing is the development of tools for the automatic reconstruction of complex 3D objects. Among various approaches, one of the most promising is Structured Light 3D scanning (SL) which combines automation and high accuracy with low cost, given the steady decrease in price of cameras and projectors. SL relies on the projection of different light patterns, by means of a video projector, on 3D object sur faces, which are recorded by one or more digital cameras. Automatic pattern identification on images allows reconstructing the shape of recorded 3D objects via triangulation of the optical rays corresponding to projector and camera pixels. Models draped with realistic phototexture may be thus also generated, reproducing both geometry and appearance of the 3D world. In this context, subject of our research is a synthesis of state-of-the-art as well as the development of...
Recent progress in coded structured light as a technique to solve the correspondence problem
Pattern Recognition, 1998
We present a survey of the most significant techniques, used in the last few years, concerning the coded structured light methods employed to get 3D information. In fact, depth perception is one of the most important subjects in computer vision. Stereovision is an attractive and widely used method, but, it is rather limited to make 3D surface maps, due to the correspondence problem. The correspondence problem can be improved using a method based on structured light concept, projecting a given pattern on the measuring surfaces. However, some relations between the projected pattern and the reflected one must be solved. This relationship can be directly found codifying the projected light, so that, each imaged region of the projected pattern carries the needed information to solve the correspondence problem.