SwissRanger SR-3000 Research Articles

RECORDING AND MODELLING OF MONUMENTS' INTERIOR SPACE USING RANGE AND OPTICAL SENSORS

Three dimensional modelling of artefacts and building interiors is a highly active research field in our days. Several techniques are being utilized to perform such a task, spanning from traditional surveying techniques and photogrammetry to structured light scanners, laser scanners and so on. New technological advancements in both hardware and software create new recording techniques, tools and approaches. In this paper we present a new recording and modelling approach based on the SwissRanger SR4000 range camera coupled with a Canon 400D dSLR camera. The hardware component of our approach consists of a fixed base, which encloses the range and SLR cameras. The two sensors are fully calibrated and registered to each other thus we were able to produce colorized point clouds acquired from the range camera. In this paper we present the initial design and calibration of the system along with experimental data regarding the accuracy of the proposed approach. We are also providing results regarding the modelling of interior spaces and artefacts accompanied with accuracy tests from other modelling approaches based on photogrammetry and laser scanning.

RECORDING AND MODELLING OF MONUMENTS' INTERIOR SPACE USING RANGE AND OPTICAL SENSORS

Abstract. Three dimensional modelling of artefacts and building interiors is a highly active research field in our days. Several techniques are being utilized to perform such a task, spanning from traditional surveying techniques and photogrammetry to structured light scanners, laser scanners and so on. New technological advancements in both hardware and software create new recording techniques, tools and approaches. In this paper we present a new recording and modelling approach based on the SwissRanger SR4000 range camera coupled with a Canon 400D dSLR camera. The hardware component of our approach consists of a fixed base, which encloses the range and SLR cameras. The two sensors are fully calibrated and registered to each other thus we were able to produce colorized point clouds acquired from the range camera. In this paper we present the initial design and calibration of the system along with experimental data regarding the accuracy of the proposed approach. We are also providing results regarding the modelling of interior spaces and artefacts accompanied with accuracy tests from other modelling approaches based on photogrammetry and laser scanning.

Breath Analysis Using a Time-of-Flight Camera and Pressure Belts.

The proper way of breathing is important for everyone. Healthy people often do not follow respiration until breathing problems start-during stress or during sport activity in physiological cases. More serious cases are stroke, injury, or surgery of the chest and others. So, learning to breathe correctly and/or breathing diagnosis is considerable for many reasons. Two novel methods of breath analysis suitable for diagnostics and rehabilitation are presented. The first technique utilizes pressure belts fastened to the patient's belly and chest, and the second method relies on a SwissRanger SR-4000 time-of-flight camera. The measurement principles are described together with the advantages and disadvantages of the applied techniques. The SwissRanger camera depth calibration is proposed to facilitate better results during the breath analysis. The methods are tested on a group of students to provide a comparison of their individual performances. As it was demonstrated, presented methods proved to work reliably. The method based on time-of-flight camera seems to be more suitable for diagnosis, while the method based on pressure belts is more suitable for rehabilitation and biofeedback applications.

Pile volume measurement by range imaging camera in indoor environment

Abstract. Range imaging (RIM) camera is recent technology in 3D location measurement. The new study areas have been emerged in measurement and data processing together with RIM camera. It has low-cost and fast measurement technique compared to the current measurement techniques. However its measurement accuracy varies according to effects resulting from the device and the environment. The direct sunlight is affect measurement accuracy of the camera. Thus, RIM camera should be used for indoor measurement. In this study gravel pile volume was measured by SwissRanger SR4000 camera. The measured volume is acquired as different 8.13% from the known.

Indoor and outdoor depth imaging of leaves with time-of-flight and stereo vision sensors: Analysis and comparison

In this article we analyze the response of Time-of-Flight (ToF) cameras (active sensors) for close range imaging under three different illumination conditions and compare the results with stereo vision (passive) sensors. ToF cameras are sensitive to ambient light and have low resolution but deliver high frame rate accurate depth data under suitable conditions. We introduce metrics for performance evaluation over a small region of interest. Based on these metrics, we analyze and compare depth imaging of leaf under indoor (room) and outdoor (shadow and sunlight) conditions by varying exposure times of the sensors. Performance of three different ToF cameras (PMD CamBoard, PMD CamCube and SwissRanger SR4000) is compared against selected stereo-correspondence algorithms (local correlation and graph cuts). PMD CamCube has better cancelation of sunlight, followed by CamBoard, while SwissRanger SR4000 performs poorly under sunlight. Stereo vision is comparatively more robust to ambient illumination and provides high resolution depth data but is constrained by texture of the object along with computational efficiency. Graph cut based stereo correspondence algorithm can better retrieve the shape of the leaves but is computationally much more expensive as compared to local correlation. Finally, we propose a method to increase the dynamic range of ToF cameras for a scene involving both shadow and sunlight exposures at the same time by taking advantage of camera flags (PMD) or confidence matrix (SwissRanger).

Comparative evaluation of range sensor accuracy for indoor mobile robotics and automated logistics applications

3D range sensing is an important topic in robotics, as it is a component in vital autonomous subsystems such as for collision avoidance, mapping and perception. The development of affordable, high frame rate and precise 3D range sensors is thus of considerable interest. Recent advances in sensing technology have produced several novel sensors that attempt to meet these requirements. This work is concerned with the development of a holistic method for accuracy evaluation of the measurements produced by such devices. A method for comparison of range sensor output to a set of reference distance measurements, without using a precise ground truth environment model, is proposed. This article presents an extensive evaluation of three novel depth sensors — the Swiss Ranger SR-4000, Fotonic B70 and Microsoft Kinect. Tests are concentrated on the automated logistics scenario of container unloading. Six different setups of box-, cylinder-, and sack-shaped goods inside a mock-up container are used to collect range measurements. Comparisons are performed against hand-crafted ground truth data, as well as against a reference actuated Laser Range Finder (aLRF) system. Additional test cases in an uncontrolled indoor environment are performed in order to evaluate the sensors’ performance in a challenging, realistic application scenario.

Lookup Table Hough Transform for Real Time Range Image Segmentation and Featureless Co-Registration

The paper addresses range image segmentation, particularly of data recorded by range cameras, such as the Microsoft Kinect and the Mesa Swissranger SR4000. These devices record range images at video frame rates and allow for acquisition of 3-dimensional measurement sequences that can be used for 3D reconstruction of indoor environments from moving platforms. The role of segmentation is twofold. First the necessary image co-registration can be based on corresponding segments, instead of corresponding point features (which is common practice currently). Secondly, the segments can be used during subsequent object modelling. By realisising that planar regions in disparity images can be modelled as linear functions of the image coordinates, having integer values for both domain and range, the paper introduces a lookup table based implementation of local Hough transform, allowing to obtain good segmentation results at high speeds.

Structural Deflection Measurement with a Range Camera

AbstractRange cameras offer great potential for the measurement of structural deformations because of their ability to directly measure video sequences of three-dimensional coordinates of entire surfaces, their compactness, and their relatively low cost compared with other active imaging technologies such as terrestrial laser scanners. Identified limitations of range cameras for high-precision metrology applications such as deformation measurement include the high (centimeter level) noise level and scene-dependent errors. This paper proposes models and methodologies to overcome these limitations and reports on the use of a SwissRanger SR4000 range camera for the measurement of deflections in concrete beams subjected to flexural load-testing. Results from three separate tests show that submillimeter precision and accuracy—assessed by comparison with estimates derived from terrestrial laser scanner data—can be achieved. The high-accuracy range camera results were realized by eliminating the systematic, scen...

View-invariant gesture recognition using 3D optical flow and harmonic motion context

This paper presents an approach for view-invariant gesture recognition. The approach is based on 3D data captured by a SwissRanger SR4000 camera. This camera produces both a depth map as well as an intensity image of a scene. Since the two information types are aligned, we can use the intensity image to define a region of interest for the relevant 3D data. This data fusion improves the quality of the motion detection and hence results in better recognition. The gesture recognition is based on finding motion primitives (temporal instances) in the 3D data. Motion is detected by a 3D version of optical flow and results in velocity annotated point clouds. The 3D motion primitives are represented efficiently by introducing motion context. The motion context is transformed into a view-invariant representation using spherical harmonic basis functions, yielding a harmonic motion context representation. A probabilistic Edit Distance classifier is applied to identify which gesture best describes a string of primitives. The approach is trained on data from one viewpoint and tested on data from a very different viewpoint. The recognition rate is 94.4% which is similar to the recognition rate when training and testing on gestures from the same viewpoint, hence the approach is indeed view-invariant.

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

This paper describes a new method for integrated range camera system self-calibration in which both traditional camera calibration parameters and rangefinder systematic error parameters are estimated simultaneously in a free-network bundle adjustment of observations to signalised targets. Its mathematical basis is collinearity and range observation equations augmented with correction models for systematic error sources identified in the data. The self-calibration results from datasets captured with two different range cameras, a SwissRanger SR3000 and a SwissRanger SR4000, are presented and analysed in detail. The method’s effectiveness is demonstrated in terms of systematic error removal and independent accuracy assessment. Up to a 54% reduction in the residual RMS was achieved by inclusion of the proposed error models in the self-calibration adjustment. An improvement of at least 74% in the RMS of object point co-ordinate differences, over that achieved without calibration or provided by the manufacturer’s software (in the case of the SR3000), was realised in an independent accuracy assessment. In addition, the effects of several influencing variables, including the range stochastic error model, the network geometry and the range measurements themselves, on key correlation mechanisms are analysed in detail.