891 resultados para Computer Imaging, Vision, Pattern Recognition and Graphics


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Duchenne muscular dystrophy (DMD) is a recessive X-linked form of muscular dystrophy characterized by progressive and irreversible degeneration of the muscles. The mdx mouse is the classical animal model for DMD, showing similar molecular and protein defects. The mdx mouse, however, does not show significant muscle weakness, and the diaphragm muscle is significantly more degenerated than skeletal muscles. In this work, magnetic resonance spectroscopy (MRS) was used to study the metabolic profile of quadriceps and diaphragm muscles from mdx and control mice. Using principal components analysis (PCA), the animals were separated into groups according to age and lineages. The classification was compared to histopathological analysis. Among the 24 metabolites identified from the nuclear MR spectra, only 19 were used by the PCA program for classification purposes. These can be important key biomarkers associated with the progression of degeneration in mdx muscles and with natural aging in control mice. Glutamate, glutamine, succinate, isoleucine, acetate, alanine and glycerol were increased in mdx samples as compared to control mice, in contrast to carnosine, taurine, glycine, methionine and creatine that were decreased. These results suggest that MRS associated with pattern recognition analysis can be a reliable tool to assess the degree of pathological and metabolic alterations in the dystrophic tissue, thereby affording the possibility of evaluation of beneficial effects of putative therapies. (C) 2012 Elsevier Inc. All rights reserved.

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Intracellular pattern recognition receptors such as the nucleotide-binding oligomerization domain (NOD)-like receptors family members are key for innate immune recognition of microbial infection and may play important roles in the development of inflammatory diseases, including rheumatic diseases. In this study, we evaluated the role of NOD1 and NOD2 on development of experimental arthritis. Ag-induced arthritis was generated in wild-type, NOD1(-/-)!, NOD2(-/-), or receptor-interacting serine-threonine kinase 2(-/-) (RIPK2(-/-)) immunized mice challenged intra-articularly with methylated BSA. Nociception was determined by electronic Von Frey test. Neutrophil recruitment and histopathological analysis of proteoglycan lost was evaluated in inflamed joints. Joint levels of inflammatory cytokine/chemokine were measured by ELISA. Cytokine (IL-6 and IL-23) and NOD2 expressions were determined in mice synovial tissue by RT-PCR. The NOD2(-/-) and RIPK2(-/-), but not NOD1(-/-), mice are protected from Ag-induced arthritis, which was characterized by a reduction in neutrophil recruitment, nociception, and cartilage degradation. NOD2/RIPK2 signaling impairment was associated with a reduction in proinflammatory cytokines and chemokines (TNF, IL-1 beta, and CXCL1/KC). IL-17 and IL-17 triggering cytokines (IL-6 and IL-23) were also reduced in the joint, but there is no difference in the percentage of CD4(+) IL-17(+) cells in the lymph node between arthritic wild-type and NOD2(-/-) mice. Altogether, these findings point to a pivotal role of the NOD2/RIPK2 signaling in the onset of experimental arthritis by triggering an IL-17-dependent joint immune response. Therefore, we could propose that NOD2 signaling is a target for the development of new therapies for the control of rheumatoid arthritis. The Journal of Immunology, 2012, 188: 5116-5122.

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In this article we propose an efficient and accurate method for fault location in underground distribution systems by means of an Optimum-Path Forest (OPF) classifier. We applied the time domains reflectometry method for signal acquisition, which was further analyzed by OPF and several other well-known pattern recognition techniques. The results indicated that OPF and support vector machines outperformed artificial neural networks and a Bayesian classifier, but OPF was much more efficient than all classifiers for training, and the second fastest for classification.

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The development of new statistical and computational methods is increasingly making it possible to bridge the gap between hard sciences and humanities. In this study, we propose an approach based on a quantitative evaluation of attributes of objects in fields of humanities, from which concepts such as dialectics and opposition are formally defined mathematically. As case studies, we analyzed the temporal evolution of classical music and philosophy by obtaining data for 8 features characterizing the corresponding fields for 7 well-known composers and philosophers, which were treated with multivariate statistics and pattern recognition methods. A bootstrap method was applied to avoid statistical bias caused by the small sample data set, with which hundreds of artificial composers and philosophers were generated, influenced by the 7 names originally chosen. Upon defining indices for opposition, skewness and counter-dialectics, we confirmed the intuitive analysis of historians in that classical music evolved according to a master apprentice tradition, while in philosophy changes were driven by opposition. Though these case studies were meant only to show the possibility of treating phenomena in humanities quantitatively, including a quantitative measure of concepts such as dialectics and opposition, the results are encouraging for further application of the approach presented here to many other areas, since it is entirely generic.

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Fractal theory presents a large number of applications to image and signal analysis. Although the fractal dimension can be used as an image object descriptor, a multiscale approach, such as multiscale fractal dimension (MFD), increases the amount of information extracted from an object. MFD provides a curve which describes object complexity along the scale. However, this curve presents much redundant information, which could be discarded without loss in performance. Thus, it is necessary the use of a descriptor technique to analyze this curve and also to reduce the dimensionality of these data by selecting its meaningful descriptors. This paper shows a comparative study among different techniques for MFD descriptors generation. It compares the use of well-known and state-of-the-art descriptors, such as Fourier, Wavelet, Polynomial Approximation (PA), Functional Data Analysis (FDA), Principal Component Analysis (PCA), Symbolic Aggregate Approximation (SAX), kernel PCA, Independent Component Analysis (ICA), geometrical and statistical features. The descriptors are evaluated in a classification experiment using Linear Discriminant Analysis over the descriptors computed from MFD curves from two data sets: generic shapes and rotated fish contours. Results indicate that PCA, FDA, PA and Wavelet Approximation provide the best MFD descriptors for recognition and classification tasks. (C) 2012 Elsevier B.V. All rights reserved.

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OBJECTIVE: To evaluate tools for the fusion of images generated by tomography and structural and functional magnetic resonance imaging. METHODS: Magnetic resonance and functional magnetic resonance imaging were performed while a volunteer who had previously undergone cranial tomography performed motor and somatosensory tasks in a 3-Tesla scanner. Image data were analyzed with different programs, and the results were compared. RESULTS: We constructed a flow chart of computational processes that allowed measurement of the spatial congruence between the methods. There was no single computational tool that contained the entire set of functions necessary to achieve the goal. CONCLUSION: The fusion of the images from the three methods proved to be feasible with the use of four free-access software programs (OsiriX, Register, MRIcro and FSL). Our results may serve as a basis for building software that will be useful as a virtual tool prior to neurosurgery.

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Abstract Background Despite new brain imaging techniques that have improved the study of the underlying processes of human decision-making, to the best of our knowledge, there have been very few studies that have attempted to investigate brain activity during medical diagnostic processing. We investigated brain electroencephalography (EEG) activity associated with diagnostic decision-making in the realm of veterinary medicine using X-rays as a fundamental auxiliary test. EEG signals were analysed using Principal Components (PCA) and Logistic Regression Analysis Results The principal component analysis revealed three patterns that accounted for 85% of the total variance in the EEG activity recorded while veterinary doctors read a clinical history, examined an X-ray image pertinent to a medical case, and selected among alternative diagnostic hypotheses. Two of these patterns are proposed to be associated with visual processing and the executive control of the task. The other two patterns are proposed to be related to the reasoning process that occurs during diagnostic decision-making. Conclusions PCA analysis was successful in disclosing the different patterns of brain activity associated with hypothesis triggering and handling (pattern P1); identification uncertainty and prevalence assessment (pattern P3), and hypothesis plausibility calculation (pattern P2); Logistic regression analysis was successful in disclosing the brain activity associated with clinical reasoning success, and together with regression analysis showed that clinical practice reorganizes the neural circuits supporting clinical reasoning.

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In this paper,we present a novel texture analysis method based on deterministic partially self-avoiding walks and fractal dimension theory. After finding the attractors of the image (set of pixels) using deterministic partially self-avoiding walks, they are dilated in direction to the whole image by adding pixels according to their relevance. The relevance of each pixel is calculated as the shortest path between the pixel and the pixels that belongs to the attractors. The proposed texture analysis method is demonstrated to outperform popular and state-of-the-art methods (e.g. Fourier descriptors, occurrence matrix, Gabor filter and local binary patterns) as well as deterministic tourist walk method and recent fractal methods using well-known texture image datasets.

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The measurement of mesozooplankton biomass in the ocean requires the use of analytical procedures that destroy the samples. Alternatively, the development of methods to estimate biomass from optical systems and appropriate conversion factors could be a compromise between the accuracy of analytical methods and the need to preserve the samples for further taxonomic studies. The conversion of the body area recorded by an optical counter or a camera, by converting the digitized area of an organism into individual biomass, was suggested as a suitable method to estimate total biomass. In this study, crustacean mesozooplankton from subtropical waters were analyzed, and individual dry weight and body area were compared. The obtained relationships agreed with other measurements of biomass obtained from a previous study in Antarctic waters. Gelatinous mesozooplankton from subtropical and Antarctic waters were also sampled and processed for body area and biomass. As expected, differences between crustacean and gelatinous plankton were highly significant. Transparent gelatinous organisms have a lower dry weight per unit area. Therefore, to estimate biomass from digitized images, pattern recognition discerning, at least, between crustaceans and gelatinous forms is required.

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The automatic extraction of biometric descriptors of anonymous people is a challenging scenario in camera networks. This task is typically accomplished making use of visual information. Calibrated RGBD sensors make possible the extraction of point cloud information. We present a novel approach for people semantic description and re-identification using the individual point cloud information. The proposal combines the use of simple geometric features with point cloud features based on surface normals.

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[EN]Gender information may serve to automatically modulate interaction to the user needs, among other applications. Within the Computer Vision community, gender classification (GC) has mainly been accomplished with the facial pattern. Periocular biometrics has recently attracted researchers attention with successful results in the context of identity recognition. But, there is a lack of experimental evaluation of the periocular pattern for GC in the wild. The aim of this paper is to study the performance of this specific facial area in the currently most challenging large dataset for the problem.

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[EN]Perceptual User Interfaces (PUIs) aim at facilitating human-computer interaction with the aid of human-like capacities (computer vision, speech recognition, etc.). In PUIs, the human face is a central element, since it conveys not only identity but also other important information, particularly with respect to the user’s mood or emotional state. This paper describes both a face detector and a smile detector for PUIs. Both are suitable for real-time interaction.

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The treatment of the Cerebral Palsy (CP) is considered as the “core problem” for the whole field of the pediatric rehabilitation. The reason why this pathology has such a primary role, can be ascribed to two main aspects. First of all CP is the form of disability most frequent in childhood (one new case per 500 birth alive, (1)), secondarily the functional recovery of the “spastic” child is, historically, the clinical field in which the majority of the therapeutic methods and techniques (physiotherapy, orthotic, pharmacologic, orthopedic-surgical, neurosurgical) were first applied and tested. The currently accepted definition of CP – Group of disorders of the development of movement and posture causing activity limitation (2) – is the result of a recent update by the World Health Organization to the language of the International Classification of Functioning Disability and Health, from the original proposal of Ingram – A persistent but not unchangeable disorder of posture and movement – dated 1955 (3). This definition considers CP as a permanent ailment, i.e. a “fixed” condition, that however can be modified both functionally and structurally by means of child spontaneous evolution and treatments carried out during childhood. The lesion that causes the palsy, happens in a structurally immature brain in the pre-, peri- or post-birth period (but only during the firsts months of life). The most frequent causes of CP are: prematurity, insufficient cerebral perfusion, arterial haemorrhage, venous infarction, hypoxia caused by various origin (for example from the ingestion of amniotic liquid), malnutrition, infection and maternal or fetal poisoning. In addition to these causes, traumas and malformations have to be included. The lesion, whether focused or spread over the nervous system, impairs the whole functioning of the Central Nervous System (CNS). As a consequence, they affect the construction of the adaptive functions (4), first of all posture control, locomotion and manipulation. The palsy itself does not vary over time, however it assumes an unavoidable “evolutionary” feature when during growth the child is requested to meet new and different needs through the construction of new and different functions. It is essential to consider that clinically CP is not only a direct expression of structural impairment, that is of etiology, pathogenesis and lesion timing, but it is mainly the manifestation of the path followed by the CNS to “re”-construct the adaptive functions “despite” the presence of the damage. “Palsy” is “the form of the function that is implemented by an individual whose CNS has been damaged in order to satisfy the demands coming from the environment” (4). Therefore it is only possible to establish general relations between lesion site, nature and size, and palsy and recovery processes. It is quite common to observe that children with very similar neuroimaging can have very different clinical manifestations of CP and, on the other hand, children with very similar motor behaviors can have completely different lesion histories. A very clear example of this is represented by hemiplegic forms, which show bilateral hemispheric lesions in a high percentage of cases. The first section of this thesis is aimed at guiding the interpretation of CP. First of all the issue of the detection of the palsy is treated from historical viewpoint. Consequently, an extended analysis of the current definition of CP, as internationally accepted, is provided. The definition is then outlined in terms of a space dimension and then of a time dimension, hence it is highlighted where this definition is unacceptably lacking. The last part of the first section further stresses the importance of shifting from the traditional concept of CP as a palsy of development (defect analysis) towards the notion of development of palsy, i.e., as the product of the relationship that the individual however tries to dynamically build with the surrounding environment (resource semeiotics) starting and growing from a different availability of resources, needs, dreams, rights and duties (4). In the scientific and clinic community no common classification system of CP has so far been universally accepted. Besides, no standard operative method or technique have been acknowledged to effectively assess the different disabilities and impairments exhibited by children with CP. CP is still “an artificial concept, comprising several causes and clinical syndromes that have been grouped together for a convenience of management” (5). The lack of standard and common protocols able to effectively diagnose the palsy, and as a consequence to establish specific treatments and prognosis, is mainly because of the difficulty to elevate this field to a level based on scientific evidence. A solution aimed at overcoming the current incomplete treatment of CP children is represented by the clinical systematic adoption of objective tools able to measure motor defects and movement impairments. A widespread application of reliable instruments and techniques able to objectively evaluate both the form of the palsy (diagnosis) and the efficacy of the treatments provided (prognosis), constitutes a valuable method able to validate care protocols, establish the efficacy of classification systems and assess the validity of definitions. Since the ‘80s, instruments specifically oriented to the analysis of the human movement have been advantageously designed and applied in the context of CP with the aim of measuring motor deficits and, especially, gait deviations. The gait analysis (GA) technique has been increasingly used over the years to assess, analyze, classify, and support the process of clinical decisions making, allowing for a complete investigation of gait with an increased temporal and spatial resolution. GA has provided a basis for improving the outcome of surgical and nonsurgical treatments and for introducing a new modus operandi in the identification of defects and functional adaptations to the musculoskeletal disorders. Historically, the first laboratories set up for gait analysis developed their own protocol (set of procedures for data collection and for data reduction) independently, according to performances of the technologies available at that time. In particular, the stereophotogrammetric systems mainly based on optoelectronic technology, soon became a gold-standard for motion analysis. They have been successfully applied especially for scientific purposes. Nowadays the optoelectronic systems have significantly improved their performances in term of spatial and temporal resolution, however many laboratories continue to use the protocols designed on the technology available in the ‘70s and now out-of-date. Furthermore, these protocols are not coherent both for the biomechanical models and for the adopted collection procedures. In spite of these differences, GA data are shared, exchanged and interpreted irrespectively to the adopted protocol without a full awareness to what extent these protocols are compatible and comparable with each other. Following the extraordinary advances in computer science and electronics, new systems for GA no longer based on optoelectronic technology, are now becoming available. They are the Inertial and Magnetic Measurement Systems (IMMSs), based on miniature MEMS (Microelectromechanical systems) inertial sensor technology. These systems are cost effective, wearable and fully portable motion analysis systems, these features gives IMMSs the potential to be used both outside specialized laboratories and to consecutive collect series of tens of gait cycles. The recognition and selection of the most representative gait cycle is then easier and more reliable especially in CP children, considering their relevant gait cycle variability. The second section of this thesis is focused on GA. In particular, it is firstly aimed at examining the differences among five most representative GA protocols in order to assess the state of the art with respect to the inter-protocol variability. The design of a new protocol is then proposed and presented with the aim of achieving gait analysis on CP children by means of IMMS. The protocol, named ‘Outwalk’, contains original and innovative solutions oriented at obtaining joint kinematic with calibration procedures extremely comfortable for the patients. The results of a first in-vivo validation of Outwalk on healthy subjects are then provided. In particular, this study was carried out by comparing Outwalk used in combination with an IMMS with respect to a reference protocol and an optoelectronic system. In order to set a more accurate and precise comparison of the systems and the protocols, ad hoc methods were designed and an original formulation of the statistical parameter coefficient of multiple correlation was developed and effectively applied. On the basis of the experimental design proposed for the validation on healthy subjects, a first assessment of Outwalk, together with an IMMS, was also carried out on CP children. The third section of this thesis is dedicated to the treatment of walking in CP children. Commonly prescribed treatments in addressing gait abnormalities in CP children include physical therapy, surgery (orthopedic and rhizotomy), and orthoses. The orthotic approach is conservative, being reversible, and widespread in many therapeutic regimes. Orthoses are used to improve the gait of children with CP, by preventing deformities, controlling joint position, and offering an effective lever for the ankle joint. Orthoses are prescribed for the additional aims of increasing walking speed, improving stability, preventing stumbling, and decreasing muscular fatigue. The ankle-foot orthosis (AFO), with a rigid ankle, are primarily designed to prevent equinus and other foot deformities with a positive effect also on more proximal joints. However, AFOs prevent the natural excursion of the tibio-tarsic joint during the second rocker, hence hampering the natural leaning progression of the whole body under the effect of the inertia (6). A new modular (submalleolar) astragalus-calcanear orthosis, named OMAC, has recently been proposed with the intention of substituting the prescription of AFOs in those CP children exhibiting a flat and valgus-pronated foot. The aim of this section is thus to present the mechanical and technical features of the OMAC by means of an accurate description of the device. In particular, the integral document of the deposited Italian patent, is provided. A preliminary validation of OMAC with respect to AFO is also reported as resulted from an experimental campaign on diplegic CP children, during a three month period, aimed at quantitatively assessing the benefit provided by the two orthoses on walking and at qualitatively evaluating the changes in the quality of life and motor abilities. As already stated, CP is universally considered as a persistent but not unchangeable disorder of posture and movement. Conversely to this definition, some clinicians (4) have recently pointed out that movement disorders may be primarily caused by the presence of perceptive disorders, where perception is not merely the acquisition of sensory information, but an active process aimed at guiding the execution of movements through the integration of sensory information properly representing the state of one’s body and of the environment. Children with perceptive impairments show an overall fear of moving and the onset of strongly unnatural walking schemes directly caused by the presence of perceptive system disorders. The fourth section of the thesis thus deals with accurately defining the perceptive impairment exhibited by diplegic CP children. A detailed description of the clinical signs revealing the presence of the perceptive impairment, and a classification scheme of the clinical aspects of perceptual disorders is provided. In the end, a functional reaching test is proposed as an instrumental test able to disclosure the perceptive impairment. References 1. Prevalence and characteristics of children with cerebral palsy in Europe. Dev Med Child Neurol. 2002 Set;44(9):633-640. 2. Bax M, Goldstein M, Rosenbaum P, Leviton A, Paneth N, Dan B, et al. Proposed definition and classification of cerebral palsy, April 2005. Dev Med Child Neurol. 2005 Ago;47(8):571-576. 3. Ingram TT. A study of cerebral palsy in the childhood population of Edinburgh. Arch. Dis. Child. 1955 Apr;30(150):85-98. 4. Ferrari A, Cioni G. The spastic forms of cerebral palsy : a guide to the assessment of adaptive functions. Milan: Springer; 2009. 5. Olney SJ, Wright MJ. Cerebral Palsy. Campbell S et al. Physical Therapy for Children. 2nd Ed. Philadelphia: Saunders. 2000;:533-570. 6. Desloovere K, Molenaers G, Van Gestel L, Huenaerts C, Van Campenhout A, Callewaert B, et al. How can push-off be preserved during use of an ankle foot orthosis in children with hemiplegia? A prospective controlled study. Gait Posture. 2006 Ott;24(2):142-151.

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The subject of this thesis is multicolour bioluminescence analysis and how it can provide new tools for drug discovery and development.The mechanism of color tuning in bioluminescent reactions is not fully understood yet but it is object of intense research and several hypothesis have been generated. In the past decade key residues of the active site of the enzyme or in the surface surrounding the active site have been identified as responsible of different color emission. Anyway since bioluminescence reaction is strictly dependent from the interaction between the enzyme and its substrate D-luciferin, modification of the substrate can lead to a different emission spectrum too. In the recent years firefly luciferase and other luciferases underwent mutagenesis in order to obtain mutants with different emission characteristics. Thanks to these new discoveries in the bioluminescence field multicolour luciferases can be nowadays employed in bioanalysis for assay developments and imaging purposes. The use of multicolor bioluminescent enzymes expanded the potential of a range of application in vitro and in vivo. Multiple analysis and more information can be obtained from the same analytical session saving cost and time. This thesis focuses on several application of multicolour bioluminescence for high-throughput screening and in vivo imaging. Multicolor luciferases can be employed as new tools for drug discovery and developments and some examples are provided in the different chapters. New red codon optimized luciferase have been demonstrated to be improved tools for bioluminescence imaging in small animal and the possibility to combine red and green luciferases for BLI has been achieved even if some aspects of the methodology remain challenging and need further improvement. In vivo Bioluminescence imaging has known a rapid progress since its first application no more than 15 years ago. It is becoming an indispensable tool in pharmacological research. At the same time the development of more sensitive and implemented microscopes and low-light imager for a better visualization and quantification of multicolor signals would boost the research and the discoveries in life sciences in general and in drug discovery and development in particular.

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Images of a scene, static or dynamic, are generally acquired at different epochs from different viewpoints. They potentially gather information about the whole scene and its relative motion with respect to the acquisition device. Data from different (in the spatial or temporal domain) visual sources can be fused together to provide a unique consistent representation of the whole scene, even recovering the third dimension, permitting a more complete understanding of the scene content. Moreover, the pose of the acquisition device can be achieved by estimating the relative motion parameters linking different views, thus providing localization information for automatic guidance purposes. Image registration is based on the use of pattern recognition techniques to match among corresponding parts of different views of the acquired scene. Depending on hypotheses or prior information about the sensor model, the motion model and/or the scene model, this information can be used to estimate global or local geometrical mapping functions between different images or different parts of them. These mapping functions contain relative motion parameters between the scene and the sensor(s) and can be used to integrate accordingly informations coming from the different sources to build a wider or even augmented representation of the scene. Accordingly, for their scene reconstruction and pose estimation capabilities, nowadays image registration techniques from multiple views are increasingly stirring up the interest of the scientific and industrial community. Depending on the applicative domain, accuracy, robustness, and computational payload of the algorithms represent important issues to be addressed and generally a trade-off among them has to be reached. Moreover, on-line performance is desirable in order to guarantee the direct interaction of the vision device with human actors or control systems. This thesis follows a general research approach to cope with these issues, almost independently from the scene content, under the constraint of rigid motions. This approach has been motivated by the portability to very different domains as a very desirable property to achieve. A general image registration approach suitable for on-line applications has been devised and assessed through two challenging case studies in different applicative domains. The first case study regards scene reconstruction through on-line mosaicing of optical microscopy cell images acquired with non automated equipment, while moving manually the microscope holder. By registering the images the field of view of the microscope can be widened, preserving the resolution while reconstructing the whole cell culture and permitting the microscopist to interactively explore the cell culture. In the second case study, the registration of terrestrial satellite images acquired by a camera integral with the satellite is utilized to estimate its three-dimensional orientation from visual data, for automatic guidance purposes. Critical aspects of these applications are emphasized and the choices adopted are motivated accordingly. Results are discussed in view of promising future developments.