A Comparison of PMD-Cameras and Stereo-Vision for the Task of Surface Reconstruction using Patchlets

Christian Beder, Bogumil Bartczak and Reinhard Koch

pdficon_large Recently real-time active 3D range cameras based on time-of-flight technology (PMD) have become available. Those cameras can be considered as a competing technique
for stereo-vision based surface reconstruction. Since those systems directly yield accurate 3d measurements, they can be used for benchmarking vision based approaches, especially in highly dynamic environments. Therefore, a comparative study of the two approaches is relevant. In this work the achievable accuracy of the two techniques, PMD and  stereo, is compared on the basis of patchlet estimation. As patchlet we define an oriented small planar 3d patch with associated surface normal. Leastsquares estimation schemes for  estimating patchlets from PMD range images as well as from a pair of stereo images are derived. It is shown, how the achivable accuracy can be estimated for both systems. Experiments  under optimal conditions for both systems are performed and the achievable accuracies are compared. It has been found that the PMD system outperformed the stereo system in terms  of achievable accuracy for distance measurements, while the estimation of normal direction is comparable for both systems.


Calibration of the Intensity-Related Distance Error of the PMD TOF-Camera

Marvin Lindner and Andreas Kolb

pdficon_largeA growing number of modern applications such as position determination, online object recognition and collision prevention depend on accurate scene analysis. A low-cost and fast alternative to standard techniques like laser scanners or stereo vision is the distance measurement with modulated, coherent infrared light based on the Photo Mixing Device (PMD) technique. This paper describes an enhanced calibration approach for PMD-based distance sensors, for which highly accurate calibration techniques have not been widely investigated yet. Compared to other known methods, our approach incorporates additional deviation errors related with the active illumination incident to the sensor pixels. The resulting calibration yields significantly more precise distance information. Furthermore, we present a simple to use, vision-based approach for the acquisition of the reference data required by any distance calibration scheme, yielding a light-weighted, on-site calibration system with little expenditure in terms of equipment.

Extrinsic and Depth Calibration of ToF-cameras

Stefan Fuchs and Gerd Hirzinger

pdficon_largeRecently, ToF-cameras have attracted attention because of their ability to generate a full 2 1/2 D depth image at video frame rate. Thus, ToF-cameras are suitable for real-time 3D tasks such as tracking, visual servoing or object pose estimation. The usability of such systems mainly depends on an accurate camera calibration. In this work a calibration process for ToF-cameras with respect to the intrinsic parameters, the depth measurement distortion and the pose of the camera to a robot’s endeffector is described. The calibration process is not only based on the monochromatic images of the camera but also uses its depth values that are generated from a chequer-board pattern. The robustness and accuracy of the presented method is assessed applying it to randomly selected shots and comparing the calibrated measurements to a ground truth obtained from a laser scanner.

Calibration and Registration for Precise Surface Reconstruction with TOF Cameras

Stefan Fuchs and Stefan May

pdficon_largeThis paper presents a method for precise surface reconstruction with time-of-flight (TOF) cameras. A novel calibration approach which simplifies the calibration task and doubles the camera’s precision is developed and compared to current calibration methods. Remaining errors are tackled by applying filter and error distributing methods. Thus, a reference object is circumferentially reconstructed with an overall mean precision of approximately 3mm in translation and 3 deg in rotation. The resulting model serves as quantification of achievable
reconstruction precision with TOF cameras. This is a major criteria for the potential analysis of this sensor technology, that is firstly demonstrated within this work.

Robust Edge Extraction for Swissranger SR-3000 Range Images

Cang Ye and GuruPrasad M. Hegde

pdficon_largeThis paper presents a new method for extracting object edges from range images obtained by a 3D range imaging sensor⎯the SwissRanger SR-3000. In range image preprocessing  tage, the method enhances object edges by using surface normal information; and it employs the Hough Transform to detect straight line features in the Normal-Enhanced Range Image  NERI). Due to the noise in the sensor’s range data, a NERI contains corrupted object surfaces that may result in unwanted edges and greatly encumber the extraction of linear features.  To alleviate this problem, a Singular Value Decomposition (SVD) filter is developed to smooth object surfaces. The efficacy of the edge extraction method is validated by experiments in  various environments.

Ludi Incipiant!

For the past three years I have been working with ToF cameras and was often confronted with the problem finding informations on the functional principle, camera devices, projects, groups and outstanding publications. So far, there is no place in the world wide web that overviews these topics.

Then, why not trying to initiate such a reviewing website, which

  • describes the technology
  • communicates news
  • accumulates publications and enables discussions
  • collects links.

As a start, the WordPress blogging tools seem to meet the requirements, especially regarding the participation. Thus, I hope some interesting and profitable discussions will evolve and say: Ludi incipiant!