The generation of 3D information from images is a key technology in many different areas, e.g. in 3D modeling and representation of architectural or heritage objects, in human body motion tracking and scanning, in 3D scene analysis of traffic scenes, in industrial applications and many more. The basic concepts rely on mathematical representations of central perspective viewing as they are widely known from photogrammetry or computer vision approaches. The objectives of these methods differ, more or less, from high precision and well-structured measurements in (industrial) photogrammetry to fully-automated non-structured applications in computer vision. Accuracy and precision is a critical issue for the 3D measurement of industrial, engineering or medical objects. As state of the art, photogrammetric multi-view measurements achieve relative precisions in the order of 1:100000 to 1:200000, and relative accuracies with respect to retraceable lengths in the order of 1:50000 to 1:100000 of the largest object diameter. In order to obtain these figures a number of influencing parameters have to be optimized. These are, besides others: physical representation of object surface (targets, texture), illumination and light sources, imaging sensors, cameras and lenses, calibration strategies (camera model), orientation strategies (bundle adjustment), image processing of homologue features (target measurement, stereo and multi-image matching), representation of object or workpiece coordinate systems and object scale. The paper discusses the above mentioned parameters and offers strategies for obtaining highest accuracy in object space. Practical examples of high-quality stereo camera measurements and multi-image applications are used to prove the relevance of high accuracy in different applications, ranging from medical navigation to static and dynamic industrial measurements. In addition, standards for accuracy verifications are presented and demonstrated by practical examples and tests.

Recently, pixel numbers and functions of consumer grade digital camera are amazingly increasing by modern semiconductor and digital technology, and there are many low-priced consumer grade digital cameras which have more than 10 mega pixels on the market in Japan. In these circumstances, digital photogrammetry using consumer grade cameras is enormously expected in various application fields. There is a large body of literature on calibration of consumer grade digital cameras and circular target location. Target location with subpixel accuracy had been investigated as a star tracker issue, and many target location algorithms have been carried out. It is widely accepted that the least squares models with ellipse fitting is the most accurate algorithm. However, there are still problems for efficient digital close range photogrammetry. These problems are reconfirmation of the target location algorithms with subpixel accuracy for consumer grade digital cameras, relationship between number of edge points along target boundary and accuracy, and an indicator for estimating the accuracy of normal digital close range photogrammetry using consumer grade cameras. With this motive, an empirical testing of several algorithms for target location with subpixel accuracy and an indicator for estimating the accuracy are investigated in this paper using real data which were acquired indoors using 7 consumer grade digital cameras which have 7.2 mega pixels to 14.7 mega pixels.

Despite the recent improvements and widespread of digital technologies and their applications in the field of Cultural Heritage, nowadays Museums and Institutions still aren't encouraged to adopt digital procedures as a standard practice to collect data upon the heritage they are called to preserve and promote. One of the main reasons for this lack can be singled out in the high costs connected with these procedures and with their increasing due to difficulties connected with digital survey of artifacts and artworks which present evident intrinsic complexities and peculiarities that cannot be reconnected to recurrences. The aim of this paper is to show the results of a research conducted in order to find the most suitable digital methodology and procedure to be adopted to collect geometric and radiometric data upon mosaics that can straightforward both the preservation of the consistency of information about its geometry and the management of huge amount of data. One of the most immediate application of digital 3d survey of mosaics is the substitution of plaster casts that are usually built to add the third dimension to pictorial or photographic surveys before restoration interventions in order to document their conservation conditions and ease reconstruction procedures. Moreover, digital 3d surveys of mosaics allow to reproduce restoration interventions in digital environment able to perform reliable preliminary evaluations; in addition, 3d reality-based models of mosaics can be used within digital catalogues or for digital exhibitions and reconstruction aims.

A self-calibration algorithm has been designed and evaluated for the calibration of a structured-light 3-D scanner based on a camera - projector pair. It aims to allow the quick calibration on the field of a reconfigurable pair which has already been calibrated accurately in laboratory. The calibration is based on the minimization of the epipolar error. Numerical and experimental tests show the correctness of the followed approach.

Time-of-flight range imaging cameras measure distance and intensity simultaneously for every pixel in an image. With the continued advancement of the technology, a wide variety of new depth sensing applications are emerging; however a number of these potential applications have stringent electrical power constraints that are difficult to meet with the current state-of-the-art systems. Sensor gain modulation contributes a significant proportion of the total image sensor power consumption, and as higher spatial resolution range image sensors operating at higher modulation frequencies (to achieve better measurement precision) are developed, this proportion is likely to increase. The authors have developed a new sensor modulation technique using resonant circuit concepts that is more power efficient than the standard mode of operation. With a proof of principle system, a 93-96% reduction in modulation drive power was demonstrated across a range of modulation frequencies from 1-11 MHz. Finally, an evaluation of the range imaging performance revealed an improvement in measurement linearity in the resonant configuration due primarily to the more sinusoidal shape of the resonant electrical waveforms, while the average precision values were comparable between the standard and resonant operating modes.

During the last years, Time-of-Flight sensors achieved a significant impact onto research fields in machine vision. In comparison to stereo vision system and laser range scanners they combine the advantages of active sensors providing accurate distance measurements and camera-based systems recording a 2D matrix at a high frame rate. Moreover low cost 3D imaging has the potential to open a wide field of additional applications and solutions in markets like consumer electronics, multimedia, digital photography, robotics and medical technologies. This paper focuses on the currently implemented 4-phase-shift algorithm in this type of sensors. The most time critical operation of the phase-shift algorithm is the arctangent function. In this paper a novel hardware implementation of the arctangent function using a reconfigurable processor system is presented and benchmarked against the state-of-the-art CORDIC arctangent algorithm. Experimental results show that the proposed algorithm is well suited for real-time processing of the range images of TOF cameras.

Several recording techniques are used together in Cultural Heritage Documentation projects. The main purpose of the documentation and conservation works is usually to generate geometric and photorealistic 3D models for both accurate reconstruction and visualization purposes. The recording approach discussed in this paper is based on the combination of photogrammetric dense matching and Terrestrial Laser Scanning (TLS) techniques. Both techniques have pros and cons, and criteria as geometry, texture, accuracy, resolution, recording and processing time are often compared. TLS techniques (time of flight or phase shift systems) are often used for the recording of large and complex objects or sites. Point cloud generation from images by dense stereo or multi-image matching can be used as an alternative or a complementary method to TLS. Compared to TLS, the photogrammetric solution is a low cost one as the acquisition system is limited to a digital camera and a few accessories only. Indeed, the stereo matching process offers a cheap, flexible and accurate solution to get 3D point clouds and textured models. The calibration of the camera allows the processing of distortion free images, accurate orientation of the images, and matching at the subpixel level. The main advantage of this photogrammetric methodology is to get at the same time a point cloud (the resolution depends on the size of the pixel on the object), and therefore an accurate meshed object with its texture. After the matching and processing steps, we can use the resulting data in much the same way as a TLS point cloud, but with really better raster information for textures. The paper will address the automation of recording and processing steps, the assessment of the results, and the deliverables (e.g. PDF-3D files). Visualization aspects of the final 3D models are presented. Two case studies with merged photogrammetric and TLS data are finally presented: - The Gallo-roman Theatre of Mandeure (France); - The Medieval Fortress of Châtel-sur-Moselle (France), where a network of underground galleries and vaults has been recorded.

We present a fast point cloud clustering technique which is suitable for outlier detection, object segmentation and region labeling for large multi-dimensional data sets. The basis is a minimal data structure similar to a kd-tree which enables us to detect connected subsets very fast. The proposed algorithms utilizing this tree structure are parallelizable which further increases the computation speed for very large data sets. The procedures given are a vital part of the data preprocessing. They improve the input data properties for a more reliable computation of surface measures, polygonal meshes and other visualization techniques. In order to show the effectiveness of our techniques we evaluate sets of point clouds from different 3D scanning devices.

The extraction of information from image and range data is one of the main research topics. In literature, several papers dealing with this topic has been already presented. In particular, several authors have suggested an integrated use of both range and image information in order to increase the reliability and the completeness of the results exploiting their complementary nature. In this paper, an integration between range and image data for the geometric reconstruction of man-made object is presented. The focus is on the edge extraction procedure performed in an integrated way exploiting both the from range and image data. Both terrestrial and aerial applications have been analysed for the façade extraction in terrestrial acquisitions and the roof outline extraction from aerial data. The algorithm and the achieved results will be described and discussed in detail.

Most of the methods described in the literature for automatic hand gesture recognition make use of classification techniques with a variety of features and classifiers. This research focuses on the frequently-used ones by performing a comparative analysis using datasets collected with a range camera. Eight different gestures were considered in this research. The features include Hu-moments, orientation histograms and hand shape associated with its distance transformation image. As classifiers, the k-nearest neighbor algorithm and the chamfer distance have been chosen. For an extensive comparison, four different databases have been collected with variation in translation, orientation and scale. The evaluation has been performed by measuring the separability of classes, and by analyzing the overall recognition rates as well as the processing times. The best result is obtained from the combination of the chamfer distance classifier and hand shape and distance transformation image, but the time analysis reveals that the corresponding processing time is not adequate for a real-time recognition.

Flexible manufacturing technologies are supporting the routine production of components with freeform surfaces in a wide variety of materials and surface finishes. Such surfaces may be exploited for both aesthetic and performance criteria for a wide range of industries, for example automotive, aircraft, small consumer goods and medial components. In order to ensure conformance between manufactured part and digital design it is necessary to understand, validate and promote best practice of the available measurement technologies. Similar, but currently less quantifiable, measurement requirements also exist in heritage, museum and fine art recording where objects can be individually hand crafted to extremely fine levels of detail. Optical 3D measurement systems designed for close range applications are typified by one or more illumination sources projecting a spot, line or structured light pattern onto a surface or surfaces of interest. Reflections from the projected light are detected in one or more imaging devices and measurements made concerning the location, intensity and optionally colour of the image. Coordinates of locations on the surface may be computed either directly from an understanding of the illumination and imaging geometry or indirectly through analysis of the spatial frequencies of the projected pattern. Regardless of sensing configuration some independent means is necessary to ensure that measurement capability will meet the requirements of a given level of object recording and is consistent for variations in surface properties and structure. As technologies mature, guidelines for best practice are emerging, most prominent at the current time being the German VDI/VDE 2634 and ISO/DIS 10360-8 guidelines. This considers state of the art capabilities for independent validation of optical non-contact measurement systems suited to the close range measurement of table top sized manufactured or crafted objects.

Time-of-flight range imaging sensors acquire an image of a scene, where in addition to standard intensity information, the range (or distance) is also measured concurrently by each pixel. Range is measured using a correlation technique, where an amplitude modulated light source illuminates the scene and the reflected light is sampled by a gain modulated image sensor. Typically the illumination source and image sensor are amplitude modulated with square waves, leading to a range measurement linearity error caused by aliased harmonic components within the correlation waveform. A simple method to improve measurement linearity by reducing the duty cycle of the illumination waveform to suppress problematic aliased harmonic components is demonstrated. If the total optical power is kept constant, the measured correlation waveform amplitude also increases at these reduced illumination duty cycles. Measurement performance is evaluated over a range of illumination duty cycles, both for a standard range imaging camera configuration, and also using a more complicated phase encoding method that is designed to cancel aliased harmonics during the sampling process. The standard configuration benefits from improved measurement linearity for illumination duty cycles around 30%, while the measured amplitude, hence range precision, is increased for both methods as the duty cycle is reduced below 50% (while maintaining constant optical power).

The presented work is conducted in the framework of the ANR-VTT PANsafer project (Towards a safer level crossing). One of the objectives of the project is to develop a video surveillance system that will be able to detect and recognize potential dangerous situation around level crossings. This paper addresses the problem of cameras positioning and orientation in order to view optimally monitored scenes. In general, adjusting cameras position and orientation is achieved experimentally and empirically by considering geometrical different configurations. This step requires a lot of time to adjust approximately the total and common fields of view of the cameras, especially when constrained environments, like level crossing environments, are considered. In order to simplify this task and to get more precise cameras positioning and orientation, we propose in this paper a method that optimizes automatically the total and common cameras fields with respect to the desired scene. Based on descriptive geometry, the method estimates the best cameras position and orientation by optimizing surfaces of 2D domains that are obtained by projecting/intersecting the field of view of each camera on/with horizontal and vertical planes. The proposed method is evaluated and tested to demonstrate its effectiveness.

Automatic image orientation of close-range image blocks is becoming a task of increasing importance in the practice of photogrammetry. Although image orientation procedures based on interactive tie point measurements do not require any preferential block structure, the use of structured sequences can help to accomplish this task in an automated way. Automatic orientation of image sequences has been widely investigated in the Computer Vision community. Here the method is generally named "Structure from Motion" (SfM), or "Structure and Motion". These refer to the simultaneous estimation of the image orientation parameters and 3D object points of a scene from a set of image correspondences. Such approaches, that generally disregard camera calibration data, do not ensure an accurate 3D reconstruction, which is a requirement for photogrammetric projects. The major contribution of SfM is therefore viewed in the photogrammetric community as a powerful tool to automatically provide a dense set of tie points as well as initial parameters for a final rigorous bundle adjustment. The paper, after a brief overview of automatic procedures for close-range image sequence orientation, will show some characteristic examples. Although powerful and reliable image orientation solutions are nowadays available at research level, there are certain questions that are still open. Thus the paper will also report some open issues, like the geometric characteristics of the sequences, scene's texture and shape, ground constraints (control points and/or free-network adjustment), feature matching techniques, outlier rejection and bundle adjustment models.

3D imaging systems are widely available and used for surveying, modeling and entertainment applications, but clear statements regarding their characteristics, performances and limitations are still missing. The VDI/VDE and the ASTME57 committees are trying to set some standards but the commercial market is not reacting properly. Since many new users are approaching these 3D recording methodologies, clear statements and information clarifying if a package or system satisfies certain requirements before investing are fundamental for those users who are not really familiar with these technologies. Recently small and portable consumer-grade active sensors came on the market, like TOF rangeimaging cameras or low-cost triangulation-based range sensor. A quite interesting active system was produced by PrimeSense and launched on the market thanks to the Microsoft Xbox project with the name of Kinect. The article reports the geometric investigation of the Kinect active sensors, considering its measurement performances, the accuracy of the retrieved range data and the possibility to use it for 3D modeling application.

Optical 3-D measurement systems based on photogrammetric methods are increasingly and successfully being applied in industrial applications, covering different sectors like automotive or aerospace industries, research facilities like particle accelerators but also emerging technologies like renewable energy. The systems are utilized throughout the whole product lifecycle - ranging from applications in R&D, development, testing, manufacturing and final quality control. Like the whole market for optical three-dimensional technologies it is a rapidly growing technology sector. As the boundaries to other optical technologies like laser triangulation sensors, white light scanning or even tactile measurement systems are narrowing, an overview of technologies used and the relevance of photogrammetric solutions in the different applications and sectors will be given.

This paper focuses on space- and time-resolved crack detection in concrete structures by combining photogrammetric techniques with acoustic emission analysis. For the photogrammetric measurements, the surface of reinforced concrete members is textured with a random pattern. A consumer-grade digital camera is used to observe the region of interest during the loading tests. In a sequence of images, cracks are visualized by detecting discrepancies in local displacement vector fields, which are obtained from matching algorithms applied to consecutive images. Critical areas of concrete samples are additionally equipped with several acoustic emission sensors to monitor the crack formation and propagation by acoustic emission analysis. The parameter-based method is used to record specific parameters in real time and enables the distinction between bending or shear cracks depending on the signal energy and duration. During the loading tests, information about the crack prolongation is used to derive the time of transition from stable to unstable phase. The acoustically detected shear cracks are monitored in the images to track growth and to stop the experiment before a critical bearing status is reached. Thus, shear cracks can be localized temporally and locally on the surface and inside the structure. In a next step, the detected cracks have to be checked for certain properties providing information about the condition of the structure. Indicators with high level significance referring to structures with no or low advance notice of failure constitute a focal point of further research.

We investigate the application of the photogrammetric approach to measuring the vibration of a model wind turbine in a sequence of stereo image pairs acquired by high speed cameras. The challenge of the photogrammetric measurement of a highly dynamic phenomenon is the efficiency of the point measurement process in a large number of images. We present a method for automated detection, tracking and measurement of photogrammetric targets in the sequence of stereo images. The tracking process exploits the knowledge of the circular motion of the rotor blades, and thus of the targets, to reduce the space of search for correspondences. The vibration is derived as the deviation of the 3D reconstructed targets from the plane defined by the first two principal components of the target positions in a complete revolution. Our experimental results show the robustness and accuracy of the proposed method for vibration measurement in a highspeed image sequence.

A three-dimensional range camera is a state-of-the-art imaging technology that has strong potential for various closerange high-precision measurement applications. One such application is the measurement of structural deformation under external loading conditions. Deformation tests have been conducted on two concrete beams with and without steel-reinforced polymer sheets in an indoor testing facility using an SR4000 range camera. The achieved measurement precision and accuracy were both within 1 mm when compared with a terrestrial laser scanner. Further testing on the concrete beam with the steel-reinforced polymer sheets has shown that a deformation as small as 3 mm can be reliably detected with a range camera with a measurement precision of 0.3 mm and an accuracy of 0.4 mm. These results clearly indicate the high metric potential of 3D range cameras in spite of their coarse imaging resolution and low (centimeterlevel) single point accuracy. The high accuracy can be achieved thanks to the differencing scheme used to derive the deflection estimates from two sets of range camera measurements, one at no-load and one of the beam in a loaded state, which eliminates the scene-dependent range biases such as scattering and multi-path errors.

The study of human equilibrium, also known as postural stability, concerns different research sectors (medicine, kinesiology, biomechanics, robotics, sport) and is usually performed employing motion analysis techniques for recording human movements and posture. A wide range of techniques and methodologies has been developed, but the choice of instrumentations and sensors depends on the requirement of the specific application. Postural stability is a topic of great interest for the maritime community, since ship motions can make demanding and difficult the maintenance of the upright stance with hazardous consequences for the safety of people onboard. The need of capturing the motion of an individual standing on a ship during its daily service does not permit to employ optical systems commonly used for human motion analysis. These sensors are not designed for operating in disadvantageous environmental conditions (water, wetness, saltiness) and with not optimal lighting. The solution proposed in this study consists in a motion acquisition system that could be easily usable onboard ships. It makes use of two different methodologies: (I) motion capture with videogrammetry and (II) motion measurement with Inertial Measurement Unit (IMU). The developed image-based motion capture system, made up of three low-cost, light and compact video cameras, was validated against a commercial optical system and then used for testing the reliability of the inertial sensors. In this paper, the whole process of planning, designing, calibrating, and assessing the accuracy of the motion capture system is reported and discussed. Results from the laboratory tests and preliminary campaigns in the field are presented.

3D models are often lacking a photorealistic appearance, due to low quality of the acquired texture, or to the complete absence of it. Moreover, especially in case of reality based models, it is often of specific interest to texture with images different from photos, like multispectral/multimodal views (InfraRed, X-rays, UV fluorescence etc), or images taken in different moments in time. In this work, a fully automatic approach for texture mapping is proposed. The method relies on the automatic extraction from the model geometry of appropriate depth maps, in form of images, whose pixels maintain an exact correspondence with vertices of the 3D model. A multiresolution method is here proposed to speed up the automatic texturing phase. Maximization of Mutual Information (MMI) is used as similarity measure as it proved to optimally exploit shared information, discarding unrelated features. 3D texturing is then applied to the portion of the model which is visualized in the texture.

High dynamic range imagery is widely used in remote sensing. With the widespread use of aerial digital cameras such as the DMC, ADS40, RMK-D, and UltraCamD, high dynamic range imaging is generally expected for generating minuteness orthophotos in digital aerial photogrammetry. However, high dynamic range images (12-bit, 4,096 gray levels) are generally compressed into an 8-bit depth digital image (256 gray levels) owing to huge amount of data and interface with peripherals such as monitors and printers. This means that a great deal of image data is eliminated from the original image, and this introduces a new shadow problem. In particular, the influence of shadows in urban areas causes serious problems when generating minuteness orthophotos and performing house detection. Therefore, shadow problems can be solved by addressing the image compression problems. There is a large body of literature on image compression techniques such as logarithmic compression and tone mapping algorithms. However, logarithmic compression tends to cause loss of details in dark and/or light areas. Furthermore, the logarithmic method intends to operate on the full scene. This means that high-resolution luminance information can not be obtained. Even though tone mapping algorithms have the ability to operate over both full scene and local scene, background knowledge is required. To resolve the shadow problem in digital aerial photogrammetry, shadow areas should be recognized and corrected automatically without the loss of luminance information. To this end, a practical shadow correction method using 12-bit real data acquired by DMC is investigated in this paper.

The elds of application for 3d cameras are very dierent, because high image frequency and determination of 3d data. Often, 3d cameras are used for mobile robotic. They are used for obstacle detection or object recognition. So they also are interesting for applications in agriculture, in combination with mobile robots. Here, in addition to 3d data, there is often a necessity to get color information for each 3d point. Unfortunately, 3d cameras do not capture any color information. Therefore, an additional sensor is necessary, such as RGB plus possibly NIR. To combine data of two dierent sensors a reference to each other, via calibration, is important. This paper presents several calibration methods and discuss their accuracy potential. Based on a spatial resection, the algorithm determines the translation and rotation between the two sensors and the inner orientation of the used sensor.

In order to resolve interior parameters of camera geometry there have been numerous development projects to automate the process. In photogrammetric community the problem solution has been sought by using coded targets and applying non-linear model in order to find accurate values for interior camera parameters. An alternative approach, popular especially in computer vision applications has been to discard the targeting and use existing geometric properties of scene to solve intrinsic parameters instead i.e. parallel lines and orthogonality of line sets. However, in most cases the parameters to be solved have been restricted to linear components of camera model. In this paper we compare the accuracy of two alternative single view calibration approaches with results from multi-station multi-image calibration. The idea is to study the accuracy and reliability of alternative mathematical models to solve intrinsic camera parameters from single view geometry.

The identification of a parallelogram in the image plane, along with the knowledge of camera parameters, allows metric properties to be recovered. This paper presents a methodology capable of estimating a rectifying homography for images of planar objects without taking any measurement on the world plane. The rectified image will have only an overall scale ambiguity. The method was implemented to create a photogrammetric package for the estimation of the proposed projective transformation. This package was also extended to compute homographic transformations with standard techniques, such as ground control points, rectangles with a known length ratio, and squares. Examples are presented using synthetic and real data acquired for different purposes, including HDR and panoramic photography. Finally, a practical test with two photogrammetric staffs was carried out to check the accuracy of the procedure, starting from the same quantities measured with an optical level.

In most close-range photogrammetry applications, the cameras are modelled as imaging systems with perspective projection combined with the lens distortion correction as proposed by Brown in 1971. In the 1980s, the calibration of video cameras received considerable attention. This required compensation for further systematic effects caused by the digitization of the analogue image signal. Modelling the image process in that manner has become the widely-applied standard since then. To take advantage of the increased field of view of individual cameras, the use of wide angle as well as fisheye lenses became common in computer vision and close-range photogrammetry, again requiring appropriate modelling of the imaging process to ensure high accuracies. A.R.T. provides real-time tracking systems with infra-red cameras, which are in some cases equipped with short focal length lenses for the purpose of increased fields of view, resulting in larger trackable object volumes. Unfortunately the lens distortion of these cameras reaches magnitudes which can not be sufficiently modelled with the customary Brown model as - mainly at high excentricities such as image corners - the calculation of the correction is not applicable. Considerations to avoid modelling these lenses as fisheye projections led to an alternate and rather pragmatic approach, where the distortion model is extended by a fourth radial distortion coefficient. Due to numeric instabilities, a stepwise camera calibration is required to achieve convergence in the bundle adjustment process. This paper presents the modified lens distortion model, describes the stepwise calibration procedure and compares results in respect to the conventional approach. The results are also compared to the approach wherein the camera lens is modelled as a fisheye projection. The introduction of a fourth radial lens distortion parameter allows the correction of lens distortion effects over the full sensor area of wide angle lenses, which increases the usable field of view of that specific camera and therefore the size of the trackable observed object volume. The approaches with the extended lens distortion model and the fisheye projection were successfully implemented and tested, and are on target to become part of the A.R.T. product range.

Although zoom lens has been widely accepted in vision system, the use of zoom lens was not general in close range photogrammetry from the view point of instability by zooming. However, with the spread of consumer grade digital cameras with integrated zoom lens, in particular long range such as ×35, digital close range photogrammetry using the camera is enormously expected in various application fields. There is a large body of literature on calibration of zoom lens. However, there is still problem for effective digital photogrammetry using the camera. The problem is practical calibration model for zoom lens, in particular correction of misalignment which is caused by zoom setting. In order to resolve instability of zoom lens, and practical use of digital close range photogrammetry using zoom lens, a new calibration model is proposed in this paper based on correction of zoom lens misalignment. Furthermore, in order to evaluate the proposed calibration model for zoom lens, calibration tests were conducted using 5 kinds of consumer grade digital camera with integrated zoom lens (×3~5), 3 kinds of long range consumer grade digital camera (×12~30) and digital SLR camera with zoom lens (×11).

The consumer digital stereo camera FinePix REAL 3D W1, which was designed to take a pair of stereo images for stereo viewing, was released in August 2009. The aim of our study is to evaluate camera calibration methods for a low-cost and easy-operation system to measure dimensions of an object on a sub-meter scale only by using a pair of stereo images acquired by the camera without any controls such as control points whose spatial locations are known or a ruler which provides the scale of the object. Three camera calibration methods were evaluated by estimation errors of lengths of line segments measured without any controls. The experiment results indicate that the best calibration method would be the method that ordinary camera calibration is first executed for each imaging unit in order to estimate its image distortion model, and then alignment between two imaging units is estimated by using two sets of the exterior orientation parameters of both imaging units obtained in the ordinary camera calibration executed previously. The experiment results indicate that the suitable calibration method would be able to provide sufficiently accurate measurement results less than 0.4 pixels on an image as well.

The continued use of existing structures is of great importance because the built environment is a huge economic and political asset, growing larger every year. The assessment of existing structures is now a major engineering task. The structural engineer is increasingly called upon to devise ways for extending the life of structures whilst observing tight cost constraints. Historical immovables which are also existing structures should be assessed elaboratively in order to preserve cultural heritage and repair historical structures. In this study, the steps carried out for generation of 3D CityGML model for a part of (North tower) the Seddülbahir fortress which is in need of urgent renovation due to specific factors (severe weather conditions, vandalism, etc.) that will be used as a base model for restoration and renovation projects and as archive data for the documentation of the fortress will be explained in detail.

The reconstruction of three dimensional objects is an increasingly important topic in many fields. Many methods are used to achieve this but among them optical full field methods are used widely due to their advantages of non contact measurement operation, fast measurement speed and automatic processing. In the measurement process, a video projector projects a lines pattern on a test surface, and a digital camera capture the image of lines pattern on it. The height distribution of surface deforms the projected line pattern and modulates them in phase domain. By applying Fourier transform analysis and phase unwrapping algorithms, the 3D profile of test surface can be reconstructed. The purposes of this paper are digital reconstruction of complex object like human face and comparison of execution time among three different phase unwrapping algorithms applied to FTP method. In addition the accuracy of measurement based on this method is compared with rightful measurement.

Fast and accurate 3D measurement of large stack-yard is important job in bulk load-and-unload and logistics management. Stack-yard holds its special characteristics as: complex and irregular shape, single surface texture and low material reflectivity, thus its 3D measurement is quite difficult to be realized by traditional non-contacting methods, such as LiDAR(LIght Detecting And Ranging) and photogrammetry. Light-section is good at the measurement of small bulk-flow but not suitable for large-scale bulk-yard yet. In the paper, an improved method based on stereo cameras and laser-line projector is proposed. The due theoretical model is composed from such three key points: corresponding point of contour edge matching in stereo imagery based on gradient and epipolar-line constraint, 3D point-set calculating for stereo imagery projected-contour edge with least square adjustment and forward intersection, then the projected 3D-contour reconstructed by RANSAC(RANdom SAmpling Consensus) and contour spatial features from 3D point-set of single contour edge. In this way, stack-yard surface can be scanned easily by the laser-line projector, and certain region's 3D shape can be reconstructed automatically by stereo cameras on an observing position. Experiment proved the proposed method is effective for bulk-yard 3D measurement in fast, automatic, reliable and accurate way.

We report on Infrared Digital Holography (IRDH) and discuss the advantages offered by this technique. Efficient recording-reconstructions of IR holograms of various objects, which differ in composition and dimensions, are shown. We demonstrate optical holographic display by means of a liquid crystal based Spatial Light Modulator (SLM), which gives the chance to get direct 3D imaging and display of the IR holograms. Finally, 3D dynamical scenes can be numerically synthesized and displayed in the visible region, using holograms of different objects.

A novel sharp features extraction method is proposed in this paper. First, we calculate the displacement between the point and its local weighted average position and we label the point with salient this value as the candidate sharp feature points and we estimate the normal direction of those candidate sharp feature points by means of local PCA methods. Then we refine the normal estimated by inferring the orientation of the points near the candidate sharp feature region and bilateral filtering in the normal field of point clouds. At last we project the displacement between point and its local weighted average position along the direction of normal .We use value of this projection as the criteria of whether a point can be labeled as sharp feature. The extracted discrete sharp feature points are represented in the form of piecewised B-Spline lines. Experiment on both real scanner point clouds and synthesized point clouds show that our method of sharp features extraction are simple to be implemented and efficient for both space and time overhead as well as it robust to the noise ,outlier and un even sample witch are inherent in the point clouds.

3D detection is an important application of Lidar. A 3D range imaging Lidar system is presented in this paper. The longitudinal resolution of 3D range imaging Lidar is poor because of the length of pulse width and gate time of ICCD, which together determine the detected longitudinal range from a single laser pulse shot. To improve the longitudinal resolution, power distribution received by one pixel of ICCD is analyzed, and a method is put forward. In this method, by setting the gate time and step interval of delay time to the value of pulse width, one object will be detected in two neighboring images, and it can be precisely located through analysis of the pixel values in the two images. The locating precision of this method is verified by experiments, and results show that the longitudinal resolution is improved by ten times, that is from 1.65m to about 0.15m. Meanwhile, the detection efficiency is reduced only a little.

This paper presents a novel color coding method which is applied to structured light measurement using fringe-pattern projections. The method is based on time coding, and reduces the projection times of fringe patterns with the same number of fringes by adding colors into the conventional fringe patterns. But the introduction of colored fringes also brings a difficulty in image processing, that is color crosstalk. To address this problem, sinusoidal fringe patterns with four colors of white, red, green and blue are used to project to the measured object surface to reduce the edge effect. Based on those ideas and methods, a three-dimensional measurement system is built, and the direct linear transform (DLT) method of calibration with lens distortion corrected by cross ratio invariance principle is used to calibrate the internal and external parameters of the system. Then the parameters of the system are optimized by the bundle adjustment method. Finally, a standard metal hemisphere with spraying is measured, and the experimental results show that with the same times of projection, the lateral measurement resolution is higher than the traditional method, and the measurement accuracy of the depth direction is about 0.27mm.

This article suggests the use of a cross-layer constraint (CLC), originated from the intrinsic relation between time slices of range-gated imaging Lidar, to facilitate the three-dimension contour reconstruction of the target. By using this physical-based method, both the effect of range ambiguity in the raw data and the dependence on the empirical image processing can be reduced, even when the Lidar system is operated on defocused state. Three outdoor scenes are fully studied to demonstrate the validity of CLC method, by using the data released by the push-broom range-gated imaging Lidar system newly developed for wide area depth mapping.