An integrated bundle adjustment approach to range camera geometric self-calibration

Lichti, Derek D.; Kim, Changjae; Jamtsho, Sonam

doi:10.1016/j.isprsjprs.2010.04.002

Cited by 44 publications

(47 citation statements)

References 24 publications

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“…The SR-4000 distance measurement accuracy is given by the manufacturer as ±0.01 m (30 MHz modulation frequency). This value has been confirmed by experimental tests, such as the ones reported in [17,18]. The distance measurement accuracy of the CamCube3.0 camera is not known, but preliminary tests performed by our group and reported in [16] The declared maximum frame rate of the SR-4000 camera is 54 fps (frames per second) and 40 fps for the CamCube3.0 at full resolution (200 × 200 pixels).…”

Section: Main Technical Specificationssupporting

confidence: 64%

“…In the last few years, several studies have reported on the performance evaluation and calibration of ToF cameras, with different aims and applications [5][6][7][8][9][10][11][12][13][14][15][16][17][18]. Since this technology has undergone rapid development, different approaches and results have been presented, which are often strictly related to the specific camera model evaluated.…”

Section: Introductionmentioning

confidence: 99%

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SR-4000 and CamCube3.0 Time of Flight (ToF) Cameras: Tests and Comparison

Piatti

Rinaudo

2012

Remote Sensing

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Abstract:In this paper experimental comparisons between two Time-of-Flight (ToF) cameras are reported in order to test their performance and to give some procedures for testing data delivered by this kind of technology. In particular, the SR-4000 camera by Mesa Imaging AG and the CamCube3.0 by PMD Technologies have been evaluated since they have good performances and are well known to researchers dealing with Time-ofFlight (ToF) cameras. After a brief overview of commercial ToF cameras available on the market and the main specifications of the tested devices, two topics are presented in this paper. First, the influence of camera warm-up on distance measurement is analyzed: a warm-up of 40 minutes is suggested to obtain the measurement stability, especially in the case of the CamCube3.0 camera, that exhibits distance measurement variations of several centimeters. Secondly, the variation of distance measurement precision variation over integration time is presented: distance measurement precisions of some millimeters are obtained in both cases. Finally, a comparison between the two cameras based on the experiments and some information about future work on evaluation of sunlight influence on distance measurements are reported.

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Section: Main Technical Specificationssupporting

confidence: 64%

Section: Introductionmentioning

confidence: 99%

SR-4000 and CamCube3.0 Time of Flight (ToF) Cameras: Tests and Comparison

Piatti

Rinaudo

2012

Remote Sensing

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“…It re-estimates the coordinate values and camera poses. Self-calibration bundle adjustment is employed because the lens distortion of range cameras cannot be ignored (Lichti et al, 2010). …”

Section: Overviewmentioning

confidence: 99%

Development of Integration and Adjustment Method for Sequential Range Images

Nagara

Fuse

2015

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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Commission V, WG V/4KEY WORDS: 3D data, Range image, Point cloud, ICP algorithm, Self-calibration bundle adjustment ABSTRACT:With increasing widespread use of three-dimensional data, the demand for simplified data acquisition is also increasing. The range camera, which is a simplified sensor, can acquire a dense-range image in a single shot; however, its measuring coverage is narrow and its measuring accuracy is limited. The former drawback had be overcome by registering sequential range images. This method, however, assumes that the point cloud is error-free. In this paper, we develop an integration method for sequential range images with error adjustment of the point cloud. The proposed method consists of ICP (Iterative Closest Point) algorithm and self-calibration bundle adjustment. The ICP algorithm is considered an initial specification for the bundle adjustment. By applying the bundle adjustment, coordinates of the point cloud are modified and the camera poses are updated. Through experimentation on real data, the efficiency of the proposed method has been confirmed.

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“…Absolute camera orientations are obtained on the basis of space resection method. Lichti et al (2010) presented the self-calibration of the range camera with respect to the rangefinder in a free-network bundle adjustment using signalized targets. Variance component estimation is applied to optimally re-weight observations iteratively.…”

Section: Introductionmentioning

confidence: 99%

Comparison of Target- And Mutual Informaton Based Calibration of Terrestrial Laser Scanner and Digital Camera for Deformation Monitoring

Omidalizarandi

Neumann

2015

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:In the current state-of-the-art, geodetic deformation analysis of natural and artificial objects (e.g. dams, bridges,...) is an ongoing research in both static and kinematic mode and has received considerable interest by researchers and geodetic engineers. In this work, due to increasing the accuracy of geodetic deformation analysis, a terrestrial laser scanner (TLS; here the Zoller+Fröhlich IMAGER 5006) and a high resolution digital camera (Nikon D750) are integrated to complementarily benefit from each other. In order to optimally combine the acquired data of the hybrid sensor system, a highly accurate estimation of the extrinsic calibration parameters between TLS and digital camera is a vital preliminary step. Thus, the calibration of the aforementioned hybrid sensor system can be separated into three single calibrations: calibration of the camera, calibration of the TLS and extrinsic calibration between TLS and digital camera. In this research, we focus on highly accurate estimating extrinsic parameters between fused sensors and target-and targetless (mutual information) based methods are applied. In target-based calibration, different types of observations (image coordinates, TLS measurements and laser tracker measurements for validation) are utilized and variance component estimation is applied to optimally assign adequate weights to the observations. Space resection bundle adjustment based on the collinearity equations is solved using Gauss-Markov and Gauss-Helmert model. Statistical tests are performed to discard outliers and large residuals in the adjustment procedure. At the end, the two aforementioned approaches are compared and advantages and disadvantages of them are investigated and numerical results are presented and discussed.

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An integrated bundle adjustment approach to range camera geometric self-calibration

Cited by 44 publications

References 24 publications

SR-4000 and CamCube3.0 Time of Flight (ToF) Cameras: Tests and Comparison

SR-4000 and CamCube3.0 Time of Flight (ToF) Cameras: Tests and Comparison

Development of Integration and Adjustment Method for Sequential Range Images

Comparison of Target- And Mutual Informaton Based Calibration of Terrestrial Laser Scanner and Digital Camera for Deformation Monitoring

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