Hybrid approach for accurate depth acquisition with structured light and stereo camera

Choi, Sung‐Hwan; Ham, Bumsub; Oh, Chang-Hwan; Choo, Hyon-Gon; Kim, Jinwoong; Sohn, Kwanghoon

doi:10.1109/bmsb.2012.6264270

Cited by 4 publications

(11 citation statements)

References 12 publications

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“…In this section, the results obtained by applying the method described above to the fusion of stereo and structured light based data sets, for the workpiece shown on Fig.2, are compared with those obtained with the technique presented in [4]. The acquired images are of size 640x480 pixels.…”

Section: Resultsmentioning

confidence: 98%

“…The results for the average distances to the reference planes, as defined in Fig.2 5 show the distance error histograms of reconstructed points registered with their corresponding planes, respectively for the proposed method and the method given in [4]. Histograms are used here to visualize the position of the points with respect to the reference planes in 3D space.…”

Section: Resultsmentioning

confidence: 99%

“…The stereoscopic pair of images is rectified before undergoing matching and reconstruction. The fusion approach presented in [4] is a technique based on computing a confidence measure (to be maximized) with respect to a given ground truth. Taking the nature of the data of the target application into account, to allow for comparison with the proposed method, the method in [4] has been adapted in order to have the same data type and to use constant settings all along the experiments.…”

Section: Resultsmentioning

confidence: 99%

“…Section 2 introduces the proposed method. Section 3 presents and discusses the experimental results, including specifically a comparison with the approach given in [4]. A conclusion and brief summary are given in section 4.…”

Section: Introductionmentioning

confidence: 98%

“…This improves the registration performance for two point sets of different characteristics. A hybrid method for acquiring precise depth maps is presented in [4]. The approach combines estimates of the depth map obtained applying both a passive and active method.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Multi-sensor data fusion for realistic and accurate 3d reconstruction

Hannachi

Kohler

Lallement

et al. 2014

2014 5th European Workshop on Visual Information Processing (EUVIP)

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In this paper, the problem of multi-sensor data fusion for 3D dimensional reconstruction/assessment of manufactured parts is investigated. For this, a method relying on cooperation of two acquisition/processing techniques (stereoscopic and structured light sensors) is presented. The stereoscopic system reconstructs the outline of the object, whereas the structured light system represents the workpiece as points that characterize its 3D surfaces. The developed approach exploits the complementarity of the two acquired data sets. To represent the whole set of measurements in a common reference frame, a fusion method is developed based on the geometric characteristics of the workpiece used to define a cost function, which allows perfect alignment of the two point sets. This is further favored by use of a camera common to the two sensory systems. Experimental results demonstrate that the proposed method outputs results, which can be meaningfully used in applications such as quality control.

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Section: Resultsmentioning

confidence: 98%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 98%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Multi-sensor data fusion for realistic and accurate 3d reconstruction

Hannachi

Kohler

Lallement

et al. 2014

2014 5th European Workshop on Visual Information Processing (EUVIP)

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Shape acquisition using a color stripe pattern with stereo structure

Chen

Wang

Chen

2014

Proceeding of the 11th World Congress on Intelligent Control and Automation

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A comparative study of multi-sensor data fusion methods for highly accurate assessment of manufactured parts

Hannachi

Kohler

Lallement

et al. 2015

Twelfth International Conference on Quality Control by Artificial Vision 2015

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3D modeling of scene contents takes an increasing importance for many computer vision based applications. In particular, industrial applications of computer vision require efficient tools for the computation of this 3D information. Routinely, stereo-vision is a powerful technique to obtain the 3D outline of imaged objects from the corresponding 2D images. As a consequence, this approach provides only a poor and partial description of the scene contents. On another hand, for structured light based reconstruction techniques, 3D surfaces of imaged objects can often be computed with high accuracy. However, the resulting active range data in this case lacks to provide data enabling to characterize the object edges. Thus, in order to benefit from the positive points of various acquisition techniques, we introduce in this paper promising approaches, enabling to compute complete 3D reconstruction based on the cooperation of two complementary acquisition and processing techniques, in our case stereoscopic and structured light based methods, providing two 3D data sets describing respectively the outlines and surfaces of the imaged objects. We present, accordingly, the principles of three fusion techniques and their comparison based on evaluation criterions related to the nature of the workpiece and also the type of the tackled application. The proposed fusion methods are relying on geometric characteristics of the workpiece, which favour the quality of the registration. Further, the results obtained demonstrate that the developed approaches are well adapted for 3D modeling of manufactured parts including free-form surfaces and, consequently quality control applications using these 3D reconstructions.

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Hybrid approach for accurate depth acquisition with structured light and stereo camera

Cited by 4 publications

References 12 publications

Multi-sensor data fusion for realistic and accurate 3d reconstruction

Multi-sensor data fusion for realistic and accurate 3d reconstruction

Shape acquisition using a color stripe pattern with stereo structure

A comparative study of multi-sensor data fusion methods for highly accurate assessment of manufactured parts

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