High-quality dense stereo vision for whole body imaging and obesity assessment

textThe prevalence of obesity has necessitated developing safe and convenient tools for timely assessing and monitoring this condition for a broad range of population. Three-dimensional (3D) body imaging has become a new mean for obesity assessment. Moreover, it generates body shape information that is meaningful for fitness, ergonomics, and personalized clothing. In the previous work of our lab, we developed a prototype active stereo vision system that demonstrated a potential to fulfill this goal. But the prototype required four computer projectors to cast artificial textures on the body which facilitate the stereo-matching on texture-deficient images (e.g., skin). This decreases the mobility of the system when used to collect a large population data. In addition, the resolution of the generated 3D~images is limited by both cameras and projectors available during the project. The study reported in this dissertation highlights our continued effort in improving the capability of 3Dbody imaging through simplified hardware for passive stereo and advanced computation techniques. The system utilizes high-resolution single-lens reflex (SLR) cameras, which became widely available lately, and is configured in a two-stance design to image the front and back surfaces of a person. A total of eight cameras are used to form four pairs of stereo units. Each unit covers a quarter of the body surface. The stereo units are individually calibrated with a specific pattern to determine cameras' intrinsic and extrinsic parameters for stereo matching. The global orientation and position of each stereo unit within a common world coordinate system is calculated through a 3Dregistration step. The stereo calibration and 3Dregistration procedures do not need to be repeated for a deployed system if the cameras' relative positions have not changed. This property contributes to the portability of the system, and tremendously alleviates the maintenance task. The image acquisition time is around two seconds for a whole-body capture. The system works in an indoor environment with a moderate ambient light. Advanced stereo computation algorithms are developed by taking advantage of high-resolution images and by tackling the ambiguity problem in stereo matching. A multi-scale, coarse-to-fine matching framework is proposed to match large-scale textures at a low resolution and refine the matched results over higher resolutions. This matching strategy reduces the complexity of the computation and avoids ambiguous matching at the native resolution. The pixel-to-pixel stereo matching algorithm follows a classic, four-step strategy which consists of matching cost computation, cost aggregation, disparity computation and disparity refinement. The system performance has been evaluated on mannequins and human subjects in comparison with other measurement methods. It was found that the geometrical measurements from reconstructed 3Dbody models, including body circumferences and whole volume, are highly repeatable and consistent with manual and other instrumental measurements (CV 0.99). The agreement of percent body fat (%BF) estimation on human subjects between stereo and dual-energy X-ray absorptiometry (DEXA) was found to be improved over the previous active stereo system, and the limits of agreement with 95% confidence were reduced by half. Our achieved %BF estimation agreement is among the lowest ones of other comparative studies with commercialized air displacement plethysmography (ADP) and DEXA. In practice, %BF estimation through a two-component model is sensitive to body volume measurement, and the estimation of lung volume could be a source of variation. Protocols for this type of measurement should still be created with an awareness of this factor.Biomedical Engineerin

High resolution 3D acquisition and modelling in cultural heritage knowledge and restoration projects: The survey of the fountain of neptune in bologna

open4noPartner: Municipality of BolognaGEORES 2019 - 2nd International Conference of geomatics and restoration, 8-10 may 2019, MilanoIn 2016, the Municipality of Bologna (Italy) has undertaken the restoration of one of the symbols of the entire city, the Fountain of Neptune, in evident state of degradation. The works have touched upon all the aspects of this complex object and the project has seen involved the Municipality and the University of Bologna, the Istituto Superiore per la Conservazione e il Restauro (ISCR) (Rome) and the Visual Computing Lab of the CNR-ISTI (Pisa), in a modern and highly multi-disciplinary approach.One of the key elements of the project was made up by the creation of an information system ad hoc developed to permit, in an innovative, efficient and user-friendly way, the collection, sharing, management and analysis of all the information and data related to diagnostics and restoration actions. The base of the information system is a very detailed 3D model of the monument, realized by means of the most modern techniques for objects 3D modelling (laser scanning, digital photogrammetry and 3D scanning) integrated together with the aim to obtain a photo-Textured 3D model characterized by a sub-millimetre precision level in the geometric description and a high perceptive fidelity of colour reproduction.The surveying activities and data processing, performed by the DICAM Geomatics group of the University of Bologna (with the collaboration of the MCM Company of Rome), are described in the paper, with considerations on the problems encountered and the procedures and solutions adopted. The information system has been developed by CNR-ISTI.openGirelli V.A.; Tini M.A.; Dellapasqua M.; Bitelli G.Girelli V.A.; Tini M.A.; Dellapasqua M.; Bitelli G

Calibration of full-waveform airborne laser scanning data for 3D object segmentation

Phd ThesisAirborne Laser Scanning (ALS) is a fully commercial technology, which has seen rapid uptake from the photogrammetry and remote sensing community to classify surface features and enhance automatic object recognition and extraction processes. 3D object segmentation is considered as one of the major research topics in the field of laser scanning for feature recognition and object extraction applications. The demand for automatic segmentation has significantly increased with the emergence of full-waveform (FWF) ALS, which potentially offers an unlimited number of return echoes. FWF has shown potential to improve available segmentation and classification techniques through exploiting the additional physical observables which are provided alongside the standard geometric information. However, use of the FWF additional information is not recommended without prior radiometric calibration, taking into consideration all the parameters affecting the backscattered energy. The main focus of this research is to calibrate the additional information from FWF to develop the potential of point clouds for segmentation algorithms. Echo amplitude normalisation as a function of local incidence angle was identified as a particularly critical aspect, and a novel echo amplitude normalisation approach, termed the Robust Surface Normal (RSN) method, has been developed. Following the radar equation, a comprehensive radiometric calibration routine is introduced to account for all variables affecting the backscattered laser signal. Thereafter, a segmentation algorithm is developed, which utilises the raw 3D point clouds to estimate the normal for individual echoes based on the RSN method. The segmentation criterion is selected as the normal vector augmented by the calibrated backscatter signals. The developed segmentation routine aims to fully integrate FWF data to improve feature recognition and 3D object segmentation applications. The routine was tested over various feature types from two datasets with different properties to assess its potential. The results are compared to those delivered through utilizing only geometric information, without the additional FWF radiometric information, to assess performance over existing methods. The results approved the potential of the FWF additional observables to improve segmentation algorithms. The new approach was validated against manual segmentation results, revealing a successful automatic implementation and achieving an accuracy of 82%

Heritage Recording and 3D Modeling with Photogrammetry and 3D Scanning

The importance of landscape and heritage recording and documentation with optical remote sensing sensors is well recognized at international level. The continuous development of new sensors, data capture methodologies and multi-resolution 3D representations, contributes significantly to the digital 3D documentation, mapping, conservation and representation of landscapes and heritages and to the growth of research in this field. This article reviews the actual optical 3D measurement sensors and 3D modeling techniques, with their limitations and potentialities, requirements and specifications. Examples of 3D surveying and modeling of heritage sites and objects are also shown throughout the paper

Illumination Invariant Outdoor Perception

This thesis proposes the use of a multi-modal sensor approach to achieve illumination invariance in images taken in outdoor environments. The approach is automatic in that it does not require user input for initialisation, and is not reliant on the input of atmospheric radiative transfer models. While it is common to use pixel colour and intensity as features in high level vision algorithms, their performance is severely limited by the uncontrolled lighting and complex geometric structure of outdoor scenes. The appearance of a material is dependent on the incident illumination, which can vary due to spatial and temporal factors. This variability causes identical materials to appear differently depending on their location. Illumination invariant representations of the scene can potentially improve the performance of high level vision algorithms as they allow discrimination between pixels to occur based on the underlying material characteristics. The proposed approach to obtaining illumination invariance utilises fused image and geometric data. An approximation of the outdoor illumination is used to derive per-pixel scaling factors. This has the effect of relighting the entire scene using a single illuminant that is common in terms of colour and intensity for all pixels. The approach is extended to radiometric normalisation and the multi-image scenario, meaning that the resultant dataset is both spatially and temporally illumination invariant. The proposed illumination invariance approach is evaluated on several datasets and shows that spatial and temporal invariance can be achieved without loss of spectral dimensionality. The system requires very few tuning parameters, meaning that expert knowledge is not required in order for its operation. This has potential implications for robotics and remote sensing applications where perception systems play an integral role in developing a rich understanding of the scene

A Cost-Effective System for Aerial 3D Thermography of Buildings

Three-dimensional (3D) imaging and infrared (IR) thermography are powerful tools in many areas in engineering and sciences. Their joint use is of great interest in the buildings sector, allowing inspection and non-destructive testing of elements as well as an evaluation of the energy efficiency. When dealing with large and complex structures, as buildings (particularly historical) generally are, 3D thermography inspection is enhanced by Unmanned Aerial Vehicles (UAV-also known as drones). The aim of this paper is to propose a simple and cost-effective system for aerial 3D thermography of buildings. Special attention is thus payed to instrument and reconstruction software choice. After a very brief introduction to IR thermography for buildings and 3D thermography, the system is described. Some experimental results are given to validate the proposal

Three-Dimensional (3D) Modelling and Optimization for Multipurpose Analysis and Representation of Ancient Statues

The technological advances that have developed in the field of threedimensional (3D) survey and modelling allow us to digitally and accurately preserve many significant heritage assets that are at risk. With regard to museum assets, extensive digitalization projects aim at achieving multilingual digital libraries accessible to everyone. A first trend is geared to the use of 3D models for further specialized studies, acquiring and processing virtual detailed copies as close as possible to the shape and contents of the real one. On the other hand, many museums look today for more interactive and immersive exhibitions, which involve the visitors’ emotions, and this has contributed to the increase in the use of virtual reality and 3D models in museums installations. In this paper, we present two case studies that belong to these scenarios. Multisensor surveys have been applied to some archeological statues preserved in two museums for multipurpose analyses and representation: a UTI test, which required high detailed data about the geometry of the object, and a communicative application, which needed instead a high level of model optimization, poor geometry, but very good representation that was achieved through remeshing tools and normal maps