This PDF file contains the front matter associated with SPIE Proceedings volume 7526, including the Title Page, Copyright information, Table of Contents, Introduction, and the Conference Committee listing.

3D shape matching and retrieval is a challenging task. In order to solve for that problem, one has to extract some relevant descriptors from the shapes. A relevant descriptor is a compact data set computed from a shape that can be quickly generated and matched while still capturing the differences between dissimilar shapes. The research work on shape matching has given rise to a variety of local and global descriptors (statistical descriptor, parametrical descriptor, transform based descriptor ...). In the last decade, symmetry analysis has received a considerable attention, since most of 3D objects exhibit that kind of feature. Symmetry analysis relies on global or local descriptor matching while introducing symmetry data into a global descriptor can greatly improve its discriminative power. Early works on symmetry analysis was limited to global symmetry. In the last years, several approaches deal with multi-scale symmetry. The symmetry scale refers to the relative volume or surface of a symmetrical region from a shape. In that case, a probability distribution is built in the space of rigid euclidean transformation by pairing some points together when their associated descriptors are similar enough. However there is no particular matching condition according to the symmetry scale and every pairs of points have the same weight when voting regardless of the symmetry scale to be considered. The symmetry scale refers to the relative volume or surface of a symmetrical region from a shape. Assuming that the larger the symmetry scale is, the larger the descriptor to be matched must be, we present and analyze in this paper a method for multi-scale mirror symmetry analysis. The method works for 3D polygonal meshes and does not need to build any 3D Image representation of the model. Moreover the method increases accuracy of the pairing stage, leading to a more reliable probability distribution, without adding more complexity.

We propose a 3D anisotropic diffusion filter for denoising and enhancing oriented data. The approach is a generalization of a previous contribution and it is based on a novel, more precise orientation estimation step. The orientation in the 3D space is computed using an asymmetric Isotropic Recursive Oriented Network (IRON) operator that can handle in a natural way junctions and corners. In the experimental section we employ a set of 3D synthetic blocks to illustrate the efficiency of the new method through quantitative and visual comparisons with other 3D-extended classical models or recently proposed 3D Partial Differential Equations (PDE).

In the face recognition problem, one of the most critical sources of variation is facial expression. This paper presents a system to overcome this issue by utilizing facial expression simulations on realistic and animatable face models that are in compliance with MPEG-4 specifications. In our system, firstly, 3D frontal face scans of the users in neutral expression and with closed mouth are taken for onetime enrollment. Those rigid face models are then converted into animatable models by warping a generic animatable model using Thin Plate Spline method. The warping is based on the facial feature points and both 2D color and 3D shape data are exploited for the automation of their extraction. The obtained models of the users can be animated by using a facial animation engine. This new attribution helps us to bring our whole database in the same "expression state" detected in a test image for better recognition results, since the disadvantage of expression variations is eliminated.

An extension of Bayesian Shape Models (BSM) to 3D space is presented. The extension is based on the inclusion of shape information into the fitting functions. Shape information consists of 3D shape descriptors they are derived from curvature, and were selected by considering the relevance of the feature. We also introduce the use of functions to define the separation of face regions. In order to extract the features, the 3D BSM is deformed iteratively by looking for the vertices that best match the shape, by using a point model distribution obtained from train dataset. As result of the fitting process, a 3D face model oriented in frontal position and segmented in 48 regions is obtained, over this model 15 landmarks are extracted. The 3D BSM was trained with 150 3D face models from two different databases, and evaluated using a leave-one-out scheme. The model segmentation and the landmark location were compared against a ground truth segmentation and point location. From this comparison it is possible to affirm that the proposed system has an accuracy of approximately one millimeter, and the orientation of the models in frontal position has an average error of more or less 1.5 degrees.

Disparity estimation can be used for eliminating redundancies between different views of an object or a scene recorded by an array of cameras which are arranged both horizontally and vertically. However, estimation of the disparity vectors is a highly time consuming process which takes most of the operation time of the multi-view video coding. Therefore, either the amount of data that is to be processed or the complexity of the coding method needs to be decreased in order to encode the multi-view video in a reasonable time. It is proven that the disparities of a point in the scene photographed by cameras which are spaced equidistantly are equal. Since there is a strong geometrical correlation of the disparity vectors, the disparity vector of a view can for most blocks be derived from the disparity vector of another view or views. A new algorithm is presented that reduces the amount of processing time needed for calculating the disparity vectors of each neighboring view except the principal ones. Different schemes are proposed for 3x3 views and they are applied to several image sequences taken from a camera-array. The experimental results show that the proposed schemes yield better results than the reference scheme while preserving the image quality and the amount of encoded data.

This paper deals with 3DTV, more especially with 3D content transmission using disparity-based format. In 3DTV, the problem of measuring the stereoscopic quality of a 3D content remains open. Depth signal degradations due to 3DTV transmission will induce new types of artifacts in the final rendered views. Whereas we have some experience regarding the issue of texture coding, the issue of depth coding consequences is rather unknown. In this paper we focus on that particular issue. For that purpose we considered LDV contents (Layered Depth Video) and performed various encoding of their depth information - i.e. depth maps plus depth occlusions layers - using MPEG-4 Part 10 AVC/H.264 MVC. We investigate the impact of depth coding artifacts on the quality of the final views. To this end, we compute the correlation between depth coding errors with the quality of the synthesized views. The criteria used for synthesized views include MSE and structural criteria such as SSIM. The criteria used for depth maps include also a topological measure in the 3D space (the Hausdorff distance). Correlations between the two criteria sets are presented. Trends in function of quantization are also discussed.

Eye-contact plays an important role for human communications in the sense that it can convey unspoken information. However, it is highly difficult to realize eye-contact in teleconferencing systems because of camera configurations. Conventional methods to overcome this difficulty mainly resorted to space-consuming optical devices such as half mirrors. In this paper, we propose an alternative approach to achieve eye-contact by techniques of arbitrary view image synthesis. In our method, multiple images captured by real cameras are converted to the virtual viewpoint (the center of the display) by homography, and evaluation of matching errors among these projected images provides the depth map and the virtual image. Furthermore, we also propose a simpler version of this method by using a single camera to save the computational costs, in which the only one real image is transformed to the virtual viewpoint based on the hypothesis that the subject is located at a predetermined distance. In this simple implementation, eye regions are separately generated by comparison with pre-captured frontal face images. Experimental results of both the methods show that the synthesized virtual images enable the eye-contact favorably.

A basic concern of computer graphic is the modeling and realistic representation of three-dimensional objects. In this paper we present our reconstruction framework which determines a polygonal surface from a set of dense points such those typically obtained from laser scanners. We deploy the concept of adaptive blobs to achieve a first volumetric representation of the object. In the next step we estimate a coarse surface using the marching cubes method. We propose to deploy a depth-first search segmentation algorithm traversing a graph representation of the obtained polygonal mesh in order to identify all connected components. A so called supervised triangulation maps the coarse surfaces onto the dense point cloud. We optimize the mesh topology using edge exchange operations. For photo-realistic visualization of objects we finally synthesize optimal low-loss textures from available scene captures of different projections. We evaluate our framework on artificial data as well as real sensed data.

A method to convert a 2D video or 2D still image into a depth map is presented. The depth map can consequently be converted into a pair of right and left images for viewing on a stereoscopic display. The depth map can be used for other applications such as multi-view generation. Our method is based on the use of an initial depth map and a bilateral filter approximated by a bilateral grid. For still images, the initial depth map is arbitrary set by default or can be chosen by the user, while for videos it is evaluated from motion estimation. Our method produces finely segmented depth maps; when converted to the appropriate format and seen on a stereoscopic display, the resulting image or video is both realistic and comfortable to watch.

Enabling robots to automatically locate and pick up randomly placed and oriented objects from a bin is an important challenge in factory automation, replacing tedious and heavy manual labor. A system should be able to recognize and locate objects with a predefined shape and estimate the position with the precision necessary for a gripping robot to pick it up. We describe a system that consists of a structured light instrument for capturing 3D data and a robust approach for object location and pose estimation. The method does not depend on segmentation of range images, but instead searches through pairs of 2D manifolds to localize candidates for object match. This leads to an algorithm that is not very sensitive to scene complexity or the number of objects in the scene. Furthermore, the strategy for candidate search is easily reconfigurable to arbitrary objects. Experiments reported in this paper show the utility of the method on a general random bin picking problem, in this paper exemplified by localization of car parts with random position and orientation. Full pose estimation is done in less than 380 ms per image. We believe that the method is applicable for a wide range of industrial automation problems where precise localization of 3D objects in a scene is needed.

In this paper, an efficient compression technique for 3D animation sequences of irregular meshes sharing the same connectivity at each frame is presented. This work is based on our "optimized pre-coded wavelet-based method". Our main contribution in this paper is using an adaptive three-dimension wavelet transform. Wavelets are important tools widely used in signal processing to make a multi resolution representation for a given signal. In case of our 3D animation sequences, we use a 3D wavelet filtering along the temporal axis to exploit the temporal coherence. This discrete 3D temporal wavelet transform (3D TWT) results in an efficient energy concentration on the low pass temporal sub bands. The discrete 3D temporal wavelet transforms (3D TWT) is more efficient than Haar wavelet and also Mallat wavelet which were used in our "optimized pre-coded wavelet-based method". The idea of our proposed technique is simple and the resulting chain is flexible. Simulation results show that our compression method provides good compression performances compared to some other efficient compression techniques.

In 3D steganography and watermarking, the synchronization of the hidden data is a major problem. We need to know where the message is embedded in order to extract the correct information. Various algorithms have been proposed for the last couple of years and we focused on a method based on Euclidean minimum spanning tree (EMST) for the mesh vertices. In this paper we analyze the sensitivity of the EMST structure in order to propose a new method more robust. We present a new theoretical analysis and we propose to visualize the robustness of the EMST. Moreover, we can apply this analysis to various applications that can be useful in 3D steganography such fragile area detection and prediction of the 3D object robustness during transmission on a noisy channel.

This paper presents a polygon soup representation for multiview data. Starting from a sequence of multi-view video plus depth (MVD) data, the proposed representation takes into account, in a unified manner, different issues such as compactness, compression, and intermediate view synthesis. The representation is built in two steps. First, a set of 3D quads is extracted using a quadtree decomposition of the depth maps. Second, a selective elimination of the quads is performed in order to reduce inter-view redundancies and thus provide a compact representation. Moreover, the proposed methodology for extracting the representation allows to reduce ghosting artifacts. Finally, an adapted compression technique is proposed that limits coding artifacts. The results presented on two real sequences show that the proposed representation provides a good trade-off between rendering quality and data compactness.

This paper addresses the efficient compression scheme of elemental image array (EIA) generated from the moving array lenslet technique (MALT) based on MPEG-4. The EIAs are picked-up by MALT controlling the spatial ray sampling of ray and which produces few EIAs that the positions of the lenslet arrays are rapidly vibrated in the lateral directions within the retention time of the afterimage of human eye. To enhance the similarity in each EIA picked-up by MALT, several EIAs obtained from MALT are regenerated by the collection of an elemental image occupied at the same position in each EIA. The newly generated each EIA has high similarity among adjacent elemental images. To illustrate the feasibility of the proposed scheme, some experiments are carried out to show the increased compression efficiency and we obtained the improved compression ratio of 12% compared to the unhandled compression scheme.

Distance is a fundamental concept when considering the information retrieval and cluster analysis of 3D information. That is, a large number of information retrieval descriptor comparison and cluster analysis algorithms are built around the very concept of the distance, such as the Mahalanobis or Manhattan distances, between points. Although not always explicitly stated, a significant proportion of these distances are, by nature, Euclidian. This implies that it is assumed that the data distribution, from a geometrical point of view, may be associated with a Euclidian flat space. In this paper, we draw attention to the fact that this association is, in many situations, not appropriate. Rather, the data should often be characterised by a Riemannian curved space. It is shown how to construct such a curved space and how to analyse its geometry from a topological point of view. The paper also illustrates how, in curved space, the distance between two points may be calculated. In addition, the consequences for information retrieval and cluster analysis algorithms are discussed.

In this work, we present a pose-invariant shape matching methodology for complete 3D object models. Our approach is based on first describing the objects with shape descriptors and then minimizing the distance between descriptors over an appropriate set of geometric transformations. Our chosen shape description methodology is the density-based framework (DBF), which is experimentally shown to be very effective in 3D object retrieval [1]. In our earlier work, we showed that density-based descriptors exhibit a permutation property that greatly reduces the equivocation of the eigenvalue-based axis labeling and moments-based polarity assignment in a computationally very efficient manner. In the present work, we show that this interesting permutation property is a consequence of the symmetry properties of regular polyhedra. Furthermore, we extend the invariance scheme to arbitrary 3D rotations by a discretization of the infinite space of 3D rotations followed by a nearest neighbor based approximate procedure employed to generate the necessary permutations.

3D object recognition and retrieval recently gained a big interest because of the limitation of the "2D-to-2D" approaches. The latter suffer from several drawbacks such as the lack of information (due for instance to occlusion), pose sensitivity, illumination changes, etc. Our main motivation is to gather both discrimination and easy interaction by allowing simple (but multiple) 2D specifications of queries and their retrieval into 3D gallery sets. We introduce a novel "2D sketch-to-3D model" retrieval framework with the following contributions: (i) first a novel generative approach for aligning and normalizing the pose of 3D gallery objects and extracting their 2D canonical views is introduced. (ii) Afterwards, robust and compact contour signatures are extracted using the set of 2D canonical views. We also introduce a pruning approach to speedup the whole search process in a coarseto- fine way. (iii) Finally, object ranking is performed using our variant of elastic dynamic programming which considers only a subset of possible matches thereby providing a considerable gain in performance for the same amount of errors. Our experiments are reported/compared through the Princeton Shape Benchmark; clearly showing the good performance of our framework w.r.t. the other approaches. An iPhone demo of this method is available and allows us to achieve "2D sketch to 3D object" querying and interaction.

View-based indexing schemes for 3D object retrieval are gaining popularity since they provide good retrieval results. These schemes are coherent with the theory that humans recognize objects based on their 2D appearances. The viewbased techniques also allow users to search with various queries such as binary images, range images and even 2D sketches. The previous view-based techniques use classical 2D shape descriptors such as Fourier invariants, Zernike moments, Scale Invariant Feature Transform-based local features and 2D Digital Fourier Transform coefficients. These methods describe each object independent of others. In this work, we explore data driven subspace models, such as Principal Component Analysis, Independent Component Analysis and Nonnegative Matrix Factorization to describe the shape information of the views. We treat the depth images obtained from various points of the view sphere as 2D intensity images and train a subspace to extract the inherent structure of the views within a database. We also show the benefit of categorizing shapes according to their eigenvalue spread. Both the shape categorization and data-driven feature set conjectures are tested on the PSB database and compared with the competitor view-based 3D shape retrieval algorithms.

Tele-presence systems will enable participants to feel like they are physically together. In order to improve this feeling, these systems are starting to include depth estimation capabilities. A typical requirement for these systems includes high definition, good quality results and low latency. Benchmarks demonstrate that stereo-matching algorithms using Belief Propagation (BP) produce the best results. The execution time of the BP algorithm in a CPU cannot satisfy real-time requirements with high-definition images. GPU-based implementations of BP algorithms are only able to work in real-time with small-medium size images because the traffic with memory limits their applicability. The inherent parallelism of the BP algorithm makes FPGA-based solutions a good choice. However, even though the memory traffic of a commercial FPGA-based ASIC-prototyping board is high, it is still not enough to comply with realtime, high definition and good immersive feeling requirements. The work presented estimates depth maps in less than 40 milliseconds for high-definition images at 30fps with 80 disparity levels. The proposed double BP topology and the new data-cost estimation improve the overall classical BP performance while they reduce the memory traffic by about 21%. Moreover, the adaptive message compression method and message distribution in memory reduce the number of memory accesses by more than 70% with an almost negligible loss of performance. The total memory traffic reduction is about 90%, demonstrating sufficient quality to be classified within the first 40 positions in the Middlebury ranking.

Range imagery provided by time-of-flight (TOF) cameras has been shown to be useful to facilitate robot navigation in several applications. Visual navigation for autonomous pipeline inspection robots is a special case of such a task, where the cramped operating environment influences the range measurements in a detrimental way. Inherent in the imaging system are also several defects that will lead to a smearing of range measurements. This paper sketches an approach for using TOF cameras as a visual navigation aid in pipelines, and addresses the challenges concerning the inherent defects in the imaging system and the impact of the operating environment. New results on our previously proposed strategy for detecting and tracking possible landmarks and obstacles in pipelines are presented. We consider an explicit model for correcting lens distortions, and use this to explain why the cylindrical pipe is perceived as a cone. A simplified model, which implicitly handles the combined effects of the environment and the camera on the measured ranges by adjusting for the conical shape, is used to map the robot's environment into an along-axis-view relative to the pipe, which facilitates obstacle traversal. Experiments using a model pipeline and a prototype camera rig are presented.

The paper presents an optical three-dimensional shape measurement system and an automatic method for assessment of pectus excavatum severity based on the measurement results. The measurement system consists of four directional modules utilizing structured light projection method (namely temporal phase shifting TPS and modified Gray code projection) to capture the shape of body surface of the patients. The measurement result is a three-dimensional point cloud representing the skin surface. The system setup is described and the typical measurement parameters are given. The automated data analysis path is explained. Its main stages are: point cloud segmentation, normalization of trunk orientation, cutting the model into slices, analysis of each slice shape, selecting the proper slice for the assessment of pectus excavatum of the patient and calculating its shape parameter. The analysis does not require any initial processing (e.g. surface fitting or mesh building) as it is conducted on raw 3-D point cloud data resulting from the measurement. A new shape parameter (I3ds) was developed that shows correlation with CT Haller Index widely used for assessment of pectus excavatum. Preliminary clinical results are presented.

In this paper a 3D shape measurement system with additional color and angular reflectance measurement capabilities is presented. The shape measurement system is based on structured light projection with the use of DLP projector. 3D shape measurement method is based on sinusoidal fringes and Gray codes projection. The color measurement system uses multispectral methods with a set of interference filters to separate spectral channels. Additionally the setup includes an array of compact light sources for measuring angular reflectance based on image analysis and 3D data processing. All three components of the integrated system use the same grayscale camera as a detector. The purpose of the system is to obtain complete information about shape, color and reflectance characteristic of measured surface, especially for cultural heritage objects in order to use in documentation, visualization, copying and storing. Some measurement results of real objects with a discussion of accuracy are presented along with future development plans.

In this paper we address the problem of crosstalk reduction for autostereoscopic displays. Crosstalk refers to the perception of one or more unwanted views in addition to the desired one. Specifically, the proposed approach consists of three different stages: a crosstalk measurement stage, where the crosstalk is modeled, a filter design stage, based on the results obtained out of the measurements, to mitigate the crosstalk effect, and a validation test carried out by means of subjective measurements performed in a controlled environment as recommended in ITU BT 500-11. Our analysis, synthesis, and subjective experiments are performed on the Alioscopy® display, which is a lenticular multiview display.

While objective and subjective quality assessment of 2D images and video have been an active research topic in the recent years, emerging 3D technologies require new quality metrics and methodologies taking into account the fundamental differences in the human visual perception and typical distortions of stereoscopic content. Therefore, this paper presents a comprehensive stereoscopic video database that contains a large variety of scenes captured using a stereoscopic camera setup consisting of two HD camcorders with different capture parameters. In addition to the video, the database also provides subjective quality scores obtained using a tailored single stimulus continuous quality scale (SSCQS) method. The resulting mean opinion scores can be used to evaluate the performance of visual quality metrics as well as for the comparison and for the design of new metrics.

The softwares Mesh and Metro are widely used for measuring geometrical differences between two surfaces. Unfortunately, those two softwares cannot be used to compute the surface-to-surface distance for huge semiregular meshes because of the memory capacity. Consequently, estimating the quality of remeshing or geometry compression algorithms cannot be done for such data. To overcome this problem, we propose an original algorithm for computing the surface-to-surface distance even for huge semi-regular meshes. The method consists in exploiting the relevant multi-level structure of a semi-regular mesh for loading successively small regions of it and computing the symmetrical distance between them and the irregular mesh. Experimentally, the results obtained with the proposed method are similar to the results obtained with the software MESH, while using a small memory size. This latter can reach only 2% of the size of the semi-regular mesh. Then, we show that our approach allows to compute the surface-to-surface distance for huge semi-regular meshes.

This paper describes a new system for sharing a 3D space on workbenches placed at different locations. It consists of flatbed-type autostereoscopic displays based on the one-dimensional (horizontal parallax only) integral imaging (1D-II) method and multi-viewpoint video cameras. Possible applications of the system include a tool for remote instruction, where an instructor can show how to assemble a product from given parts to a worker who is not in front of the instructor but in a different room or factory. The idea of sharing the 3D space at different locations is not new. In the previous applications such as mixed reality, however, since the depth of the reconstructed 3D space was not clearly restricted, it is difficult to improve the image quality of the reconstructed space. In the application presented in this paper, we can obtain a reasonable level of the image quality because the depth of the reconstructed space is clearly limited by the size of the parts on the 3D workbench. A new multi-viewpoint video camera was designed for the application. In this design, each image sensor was placed parallel to the lens with a shift in each direction of the XY coordinate system in a horizontal plane and only a limited region of each image was used to reconstruct the 3D space. An experimental system called the "3D hand-area space sharing system" was implemented using integral imaging 3D displays as well as multi-viewpoint video cameras. As a result, we ascertained that larger display, namely, 8K4K, and interpolation technology are necessary for a multi-viewpoint video camera for the 3D hand-area space sharing system.

An algorithm is presented to multiplex discrete disparity layers to a stack of screen images for different 3d display technologies. This approach enabled the description of a 3d display by just setting few parameters. After more than a century of intense 3d development there is a diversity of 3d displays. The representation of 3d information in these devices can be very different. Regardless of the diversity, all representation technologies can be described by a number of 2d images. The screen images are specific combinations of the image sequence. The combination rule by using the universal 4dimensional formula is adapted for a certain display type. The formula parameters are illustrated by samples for the main groups of 3d displays: stereoscopic, autostereoscopic and volumetric. With the same input image sequence, samples are calculated for diverse output systems. Also, some matrices are presented to show the influence of various parameters. Furthermore it is demonstrated that the modification of some parameters can change the 3d representation without any modification of the device or the input images. Such effects can be used for the correction of the 3d impression in single 3d systems and multi display solutions (i.e. 3d walls).

Video games are more and more controlled by the real movements of the player. However, the player is constrained by the system devices, imposing a limited vocabulary of actions associated with a set of unnatural movements. To introduce more entertaining video games to players, a component-based architecture is proposed. It has been acknowledged as the starting point for the development of adaptive applications based on the hypothesis of a high level dialogue between the system and the player. The system adaptability relies on interpretation mechanisms of the player behaviors. These behaviors are defined through the representation of the real movements of the player who freely interacts with the 3D elements composing an immersive virtual environment, following a given game scenario. The efficient interpretation of the player movements relies on the introduction in the system of the management of the scene's context. The contextual information not only helps to determine the true meaning of an observed behavior but also makes the system to adapt its processes regarding this interpretation, while managing its hardware and software resources efficiently. A commercial motion capture interface has been enhanced by the elaboration of such a system.

Three-dimensional shape of pulsatile tissue due to blood flow, which is one of key diagnostic features in ischemia, has been constructed from 2D ultrasonic movies for assisting clinical diagnosis. The 2D ultrasonic movies (640x480pixels/frame, 8bits/pixel, 33ms/frame) were taken with a conventional ultrasonic apparatus and an ultrasonic probe, while measuring the probe orientations with a compact tilt-sensor. The 2D images of pulsatile strength were obtained from each 2D ultrasonic movie by evaluating a heartbeat-frequency component calculated by Fourier transform of a series of pixel values sampled at each pixel. The 2D pulsatile images were projected into a 3D domain to obtain a 3D grid of pulsatile strength according to the probe orientations. The 3D shape of pulsatile tissue was constructed by determining the iso-surfaces of appropriate strength in the 3D grid. The shapes of pulsatile tissue examined in neonatal crania clearly represented the 3D structures of several arteries such as middle cerebral artery, which is useful for diagnosis of ischemic diseases. Since our technique is based on feature extraction in tissue dynamics, it is also useful for homogeneous tissue, for which conventional 3D ultrasonogram is unsuitable due to unclear tissue boundary.

In this paper a fully automated 3D shape measurement and processing method is presented. It assumes that positioning of measurement head in relation to measured object can be realized by specialized computer-controlled manipulator. On the base of existing 3D scans, the proposed method calculates "next best view" position for measurement head. All 3D data processing (filtering, ICP based fitting and final views integration) is performed automatically. Final 3D model is created on the base of user specified parameters like accuracy of surface representation or density of surface sampling. Exemplary system that implements all mentioned functionalities will be presented. The goal of this system is to automatically (without any user attention) and rapidly (from days and weeks to hours) measure whole object with some limitations to its properties: maximum measurement volume is described as a cylinder with 2,5m height and 1m radius, maximum object's weight is 2 tons. Measurement head is automatically calibrated by the system and its possible working volume starts from 120mm x 80mm x 60mm and ends up to 1,2m x 0,8m x 0,6m. Exemplary measurement result is presented.

The production of 3D realistic map databases is a matter of increasing interest. An approach based on the fusion of heterogeneous 3D representations was studied in previous works. Three methods of rigid registration were tested as well as the behaviors of those algorithms. One of the most difficult problems is the quantitative evaluation of 3D registration. In this term we propose a new quantitative evaluation method based on reference features comparison to improve and compare the accuracy of the registration methods.