Development of a real-time full-field range imaging system

This article describes the development of a full-field range imaging system employing a high frequency amplitude modulated light source and image sensor. Depth images are produced at video frame rates in which each pixel in the image represents distance from the sensor to objects in the scene. The various hardware subsystems are described as are the details about the firmware and software implementation for processing the images in real-time. The system is flexible in that precision can be traded off for decreased acquisition time. Results are reported to illustrate this versatility for both high-speed (reduced precision) and high-precision operating modes

Anatomically Constrained Video-CT Registration via the V-IMLOP Algorithm

Functional endoscopic sinus surgery (FESS) is a surgical procedure used to treat acute cases of sinusitis and other sinus diseases. FESS is fast becoming the preferred choice of treatment due to its minimally invasive nature. However, due to the limited field of view of the endoscope, surgeons rely on navigation systems to guide them within the nasal cavity. State of the art navigation systems report registration accuracy of over 1mm, which is large compared to the size of the nasal airways. We present an anatomically constrained video-CT registration algorithm that incorporates multiple video features. Our algorithm is robust in the presence of outliers. We also test our algorithm on simulated and in-vivo data, and test its accuracy against degrading initializations.Comment: 8 pages, 4 figures, MICCA

Probabilistic Search for Object Segmentation and Recognition

The problem of searching for a model-based scene interpretation is analyzed within a probabilistic framework. Object models are formulated as generative models for range data of the scene. A new statistical criterion, the truncated object probability, is introduced to infer an optimal sequence of object hypotheses to be evaluated for their match to the data. The truncated probability is partly determined by prior knowledge of the objects and partly learned from data. Some experiments on sequence quality and object segmentation and recognition from stereo data are presented. The article recovers classic concepts from object recognition (grouping, geometric hashing, alignment) from the probabilistic perspective and adds insight into the optimal ordering of object hypotheses for evaluation. Moreover, it introduces point-relation densities, a key component of the truncated probability, as statistical models of local surface shape.Comment: 18 pages, 5 figure

Fitting a 3D Morphable Model to Edges: A Comparison Between Hard and Soft Correspondences

We propose a fully automatic method for fitting a 3D morphable model to single face images in arbitrary pose and lighting. Our approach relies on geometric features (edges and landmarks) and, inspired by the iterated closest point algorithm, is based on computing hard correspondences between model vertices and edge pixels. We demonstrate that this is superior to previous work that uses soft correspondences to form an edge-derived cost surface that is minimised by nonlinear optimisation.Comment: To appear in ACCV 2016 Workshop on Facial Informatic

Extracellular electrical signals in a neuron-surface junction: model of heterogeneous membrane conductivity

Signals recorded from neurons with extracellular planar sensors have a wide range of waveforms and amplitudes. This variety is a result of different physical conditions affecting the ion currents through a cellular membrane. The transmembrane currents are often considered by macroscopic membrane models as essentially a homogeneous process. However, this assumption is doubtful, since ions move through ion channels, which are scattered within the membrane. Accounting for this fact, the present work proposes a theoretical model of heterogeneous membrane conductivity. The model is based on the hypothesis that both potential and charge are distributed inhomogeneously on the membrane surface, concentrated near channel pores, as the direct consequence of the inhomogeneous transmembrane current. A system of continuity equations having non-stationary and quasi-stationary forms expresses this fact mathematically. The present work performs mathematical analysis of the proposed equations, following by the synthesis of the equivalent electric element of a heterogeneous membrane current. This element is further used to construct a model of the cell-surface electric junction in a form of the equivalent electrical circuit. After that a study of how the heterogeneous membrane conductivity affects parameters of the extracellular electrical signal is performed. As the result it was found that variation of the passive characteristics of the cell-surface junction, conductivity of the cleft and the cleft height, could lead to different shapes of the extracellular signals

Biometrics in forensic science: challenges, lessons and new technologies

Biometrics has historically found its natural mate in Forensics. The first applications found in the literature and over cited so many times, are related to biometric measurements for the identification of multiple offenders from some of their biometric and anthropometric characteristics (tenprint cards) and individualization of offender from traces found on crime-scenes (e.g. fingermarks, earmarks, bitemarks, DNA). From sir Francis Galton, to the introduction of AFIS systems in the scientific laboratories of police departments, Biometrics and Forensics have been "dating" with alternate results and outcomes. As a matter of facts there are many technologies developed under the "Biometrics umbrella" which may be optimised to better impact several Forensic scenarios and criminal investigations. At the same time, there is an almost endless list of open problems and processes in Forensics which may benefit from the introduction of tailored Biometric technologies. Joining the two disciplines, on a proper scientific ground, may only result in the success for both fields, as well as a tangible benefit for the society. A number of Forensic processes may involve Biometric-related technologies, among them: Evidence evaluation, Forensic investigation, Forensic Intelligence, Surveillance, Forensic ID management and Verification.\ud The COST Action IC1106 funded by the European Commission, is trying to better understand how Biometric and Forensics synergies can be exploited within a pan-European scientific alliance which extends its scope to partners from USA, China and Australia.\ud Several results have been already accomplished pursuing research in this direction. Notably the studies in 2D and 3D face recognition have been gradually applied to the forensic investigation process. In this paper a few solutions will be presented to match 3D face shapes along with some experimental results

Asynchronous, Photometric Feature Tracking using Events and Frames

We present a method that leverages the complementarity of event cameras and standard cameras to track visual features with low-latency. Event cameras are novel sensors that output pixel-level brightness changes, called "events". They offer significant advantages over standard cameras, namely a very high dynamic range, no motion blur, and a latency in the order of microseconds. However, because the same scene pattern can produce different events depending on the motion direction, establishing event correspondences across time is challenging. By contrast, standard cameras provide intensity measurements (frames) that do not depend on motion direction. Our method extracts features on frames and subsequently tracks them asynchronously using events, thereby exploiting the best of both types of data: the frames provide a photometric representation that does not depend on motion direction and the events provide low-latency updates. In contrast to previous works, which are based on heuristics, this is the first principled method that uses raw intensity measurements directly, based on a generative event model within a maximum-likelihood framework. As a result, our method produces feature tracks that are both more accurate (subpixel accuracy) and longer than the state of the art, across a wide variety of scenes.Comment: 22 pages, 15 figures, Video: https://youtu.be/A7UfeUnG6c

Experimental investigation on camera calibration for 3D photogrammetric scanning of micro-features for micrometric resolution

[EN] Recently, it has been demonstrated that photogrammetry can be used for the measurement of small objects with micro-features, with good results and lower cost, compared to other established techniques such as interferometry, conoscopic holography, and 3D microscopy. Calibration is a critical step in photogrammetry and the classical pinhole camera model has been tested for magnifications lower than 2×. At higher magnification levels, because of the reduction of the depth of field (DOF), images can lead to calibration data with low reprojection errors. However, this could lead to bad results in the 3D reconstruction. With the aim of verifying the possibility of applying the camera model to magnifications higher than 2×, experiments have been conducted using reflex cameras with 60 mm macro lens, equipped with the combination of three extension tubes, corresponding to 2.06, 2.23, and 2.4 magnification levels, respectively. Experiments consisted of repeating calibration five times for each configuration and testing each calibration model, measuring two artifacts with different geometrical complexity. The calibration results have shown good repeatability of a subset of the internal calibration parameters. Despite the differences in the calibration reprojection error (RE), the quality of the photogrammetric 3D models retrieved was stable and satisfying. The experiment demonstrated the possibilities of the photogrammetric system presented, equipped to very high magnification levels, to retrieve accurate 3D reconstruction of micro-features with uncertainties of few micrometers, comparable with industry s expensive state-of-the-art technologies.Percoco, G.; Guerra, MG.; Sánchez Salmerón, AJ.; Galantucci, LM. (2017). Experimental investigation on camera calibration for 3D photogrammetric scanning of micro-features for micrometric resolution. 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Optical techniques for 3D surface reconstruction in computer-assisted laparoscopic surgery

One of the main challenges for computer-assisted surgery (CAS) is to determine the intra-opera- tive morphology and motion of soft-tissues. This information is prerequisite to the registration of multi-modal patient-specific data for enhancing the surgeon’s navigation capabilites by observ- ing beyond exposed tissue surfaces and for providing intelligent control of robotic-assisted in- struments. In minimally invasive surgery (MIS), optical techniques are an increasingly attractive approach for in vivo 3D reconstruction of the soft-tissue surface geometry. This paper reviews the state-of-the-art methods for optical intra-operative 3D reconstruction in laparoscopic surgery and discusses the technical challenges and future perspectives towards clinical translation. With the recent paradigm shift of surgical practice towards MIS and new developments in 3D opti- cal imaging, this is a timely discussion about technologies that could facilitate complex CAS procedures in dynamic and deformable anatomical regions