Multi-robot cooperative stereo for outdoor scenarios

13th International Conference on Autonomous Robot Systems (Robotica), 2013

Vidéosurveillance intelligente pour la détection de chutes chez les personnes âgées

Les pays industrialisés comme le Canada doivent faire face au vieillissement de leur population. En particulier, la majorité des personnes âgées, vivant à domicile et souvent seules, font face à des situations à risques telles que des chutes. Dans ce contexte, la vidéosurveillance est une solution innovante qui peut leur permettre de vivre normalement dans un environnement sécurisé. L’idée serait de placer un réseau de caméras dans l’appartement de la personne pour détecter automatiquement une chute. En cas de problème, un message pourrait être envoyé suivant l’urgence aux secours ou à la famille via une connexion internet sécurisée. Pour un système bas coût, nous avons limité le nombre de caméras à une seule par pièce ce qui nous a poussé à explorer les méthodes monoculaires de détection de chutes. Nous avons d’abord exploré le problème d’un point de vue 2D (image) en nous intéressant aux changements importants de la silhouette de la personne lors d’une chute. Les données d’activités normales d’une personne âgée ont été modélisées par un mélange de gaussiennes nous permettant de détecter tout événement anormal. Notre méthode a été validée à l’aide d’une vidéothèque de chutes simulées et d’activités normales réalistes. Cependant, une information 3D telle que la localisation de la personne par rapport à son environnement peut être très intéressante pour un système d’analyse de comportement. Bien qu’il soit préférable d’utiliser un système multi-caméras pour obtenir une information 3D, nous avons prouvé qu’avec une seule caméra calibrée, il était possible de localiser une personne dans son environnement grâce à sa tête. Concrêtement, la tête de la personne, modélisée par une ellipsoide, est suivie dans la séquence d’images à l’aide d’un filtre à particules. La précision de la localisation 3D de la tête a été évaluée avec une bibliothèque de séquence vidéos contenant les vraies localisations 3D obtenues par un système de capture de mouvement (Motion Capture). Un exemple d’application utilisant la trajectoire 3D de la tête est proposée dans le cadre de la détection de chutes. En conclusion, un système de vidéosurveillance pour la détection de chutes avec une seule caméra par pièce est parfaitement envisageable. Pour réduire au maximum les risques de fausses alarmes, une méthode hybride combinant des informations 2D et 3D pourrait être envisagée.

Visual sensor fusion for active security in robotic industrial environments

This work presents a method of information fusion involving data captured by both a standard CCD camera and a ToF camera to be used in the detection of the proximity between a manipulator robot and a human. Both cameras are assumed to be located above the work area of an industrial robot. The fusion of colour images and time of light information makes it possible to know the 3D localization of objects with respect to a world coordinate system. At the same time this allows to know their colour information. Considering that ToF information given by the range camera contains innacuracies including distance error, border error, and pixel saturation, some corrections over the ToF information are proposed and developed to improve the results. The proposed fusion method uses the calibration parameters of both cameras to reproject 3D ToF points, expressed in a common coordinate system for both cameras and a robot arm, in 2D colour images. In addition to this, using the 3D information, the motion detection in a robot industrial environment is achieved, and the fusion of information is applied to the foreground objects previously detected. This combination of information results in a matrix that links colour and 3D information, giving the possibility of characterising the object by its colour in addition to its 3D localization. Further development of these methods will make it possible to identify objects and their position in the real world, and to use this information to prevent possible collisions between the robot and such objects.

Visual sensor fusion for active security in robotic industrial environments

This work presents a method of information fusion involving data captured by both a standard charge-coupled device (CCD) camera and a time-of-flight (ToF) camera to be used in the detection of the proximity between a manipulator robot and a human. Both cameras are assumed to be located above the work area of an industrial robot. The fusion of colour images and time-of-flight information makes it possible to know the 3D localization of objects with respect to a world coordinate system. At the same time, this allows to know their colour information. Considering that ToF information given by the range camera contains innacuracies including distance error, border error, and pixel saturation, some corrections over the ToF information are proposed and developed to improve the results. The proposed fusion method uses the calibration parameters of both cameras to reproject 3D ToF points, expressed in a common coordinate system for both cameras and a robot arm, in 2D colour images. In addition to this, using the 3D information, the motion detection in a robot industrial environment is achieved, and the fusion of information is applied to the foreground objects previously detected. This combination of information results in a matrix that links colour and 3D information, giving the possibility of characterising the object by its colour in addition to its 3D localisation. Further development of these methods will make it possible to identify objects and their position in the real world and to use this information to prevent possible collisions between the robot and such objects.

3D Intervertebral Disc Localization and Segmentation from MR Images by Data-Driven Regression and Classification

In this paper we propose a new fully-automatic method for localizing and segmenting 3D intervertebral discs from MR images, where the two problems are solved in a unified data-driven regression and classification framework. We estimate the output (image displacements for localization, or fg/bg labels for segmentation) of image points by exploiting both training data and geometric constraints simultaneously. The problem is formulated in a unified objective function which is then solved globally and efficiently. We validate our method on MR images of 25 patients. Taking manually labeled data as the ground truth, our method achieves a mean localization error of 1.3 mm, a mean Dice metric of 87%, and a mean surface distance of 1.3 mm. Our method can be applied to other localization and segmentation tasks.

Localization and Segmentation of 3D Intervertebral Discs in MR Images by Data Driven Estimation

This paper addresses the problem of fully-automatic localization and segmentation of 3D intervertebral discs (IVDs) from MR images. Our method contains two steps, where we first localize the center of each IVD, and then segment IVDs by classifying image pixels around each disc center as foreground (disc) or background. The disc localization is done by estimating the image displacements from a set of randomly sampled 3D image patches to the disc center. The image displacements are estimated by jointly optimizing the training and test displacement values in a data-driven way, where we take into consideration both the training data and the geometric constraint on the test image. After the disc centers are localized, we segment the discs by classifying image pixels around disc centers as background or foreground. The classification is done in a similar data-driven approach as we used for localization, but in this segmentation case we are aiming to estimate the foreground/background probability of each pixel instead of the image displacements. In addition, an extra neighborhood smooth constraint is introduced to enforce the local smoothness of the label field. Our method is validated on 3D T2-weighted turbo spin echo MR images of 35 patients from two different studies. Experiments show that compared to state of the art, our method achieves better or comparable results. Specifically, we achieve for localization a mean error of 1.6-2.0 mm, and for segmentation a mean Dice metric of 85%-88% and a mean surface distance of 1.3-1.4 mm.

Application of Visual-Inertial SLAM for 3D Mapping of Underground Environments

The underground scenarios are one of the most challenging environments for accurate and precise 3d mapping where hostile conditions like absence of Global Positioning Systems, extreme lighting variations and geometrically smooth surfaces may be expected. So far, the state-of-the-art methods in underground modelling remain restricted to environments in which pronounced geometric features are abundant. This limitation is a consequence of the scan matching algorithms used to solve the localization and registration problems. This paper contributes to the expansion of the modelling capabilities to structures characterized by uniform geometry and smooth surfaces, as is the case of road and train tunnels. To achieve that, we combine some state of the art techniques from mobile robotics, and propose a method for 6DOF platform positioning in such scenarios, that is latter used for the environment modelling. A visual monocular Simultaneous Localization and Mapping (MonoSLAM) approach based on the Extended Kalman Filter (EKF), complemented by the introduction of inertial measurements in the prediction step, allows our system to localize himself over long distances, using exclusively sensors carried on board a mobile platform. By feeding the Extended Kalman Filter with inertial data we were able to overcome the major problem related with MonoSLAM implementations, known as scale factor ambiguity. Despite extreme lighting variations, reliable visual features were extracted through the SIFT algorithm, and inserted directly in the EKF mechanism according to the Inverse Depth Parametrization. Through the 1-Point RANSAC (Random Sample Consensus) wrong frame-to-frame feature matches were rejected. The developed method was tested based on a dataset acquired inside a road tunnel and the navigation results compared with a ground truth obtained by post-processing a high grade Inertial Navigation System and L1/L2 RTK-GPS measurements acquired outside the tunnel. Results from the localization strategy are presented and analyzed.

High throughput 3D super-resolution microscopy reveals Caulobacter crescentus in vivo Z-ring organization.

We created a high-throughput modality of photoactivated localization microscopy (PALM) that enables automated 3D PALM imaging of hundreds of synchronized bacteria during all stages of the cell cycle. We used high-throughput PALM to investigate the nanoscale organization of the bacterial cell division protein FtsZ in live Caulobacter crescentus. We observed that FtsZ predominantly localizes as a patchy midcell band, and only rarely as a continuous ring, supporting a model of "Z-ring" organization whereby FtsZ protofilaments are randomly distributed within the band and interact only weakly. We found evidence for a previously unidentified period of rapid ring contraction in the final stages of the cell cycle. We also found that DNA damage resulted in production of high-density continuous Z-rings, which may obstruct cytokinesis. Our results provide a detailed quantitative picture of in vivo Z-ring organization.

MRI visualized neo-intimal dissection and co-localization of novel apoptotic markers apolipoprotein C-1, ceramide and caspase-3 in a Watanabe hyperlipidemic rabbit model

PURPOSE: Apoptotic arterial wall vascular smooth muscle cell death is known to contribute to plaque vulnerability and rupture. Novel apoptotic markers like apolipoprotein C-I have been implicated in apoptotic human vascular smooth muscle cell death via recruiting a neutral sphingomyelinase (N-SMase)-ceramide pathway. In vivo relevance of these observations in an animal model of plaque rupture has not been shown. METHODS AND RESULTS: Using Watanabe rabbits, we investigated three different groups (group 1, three normal Watanabe rabbits; group 2, six Watanabe rabbits fed with high cholesterol diet for 3 months; group 3, five Watanabe rabbits with similar diet but additional endothelial denudation). We followed progression of atherosclerosis to pharmacologically induced plaque rupture non-invasively using novel 3D magnetic resonance Fast-Field-Echo angiography (TR=7.2, TE=3.6 ms, matrix=512 x 512) and Fast-Spin-Echo vessel wall imaging methods (TR=3 heart beats, TE=10.5 ms, matrix=304 x 304) on 1.5 T MRI. MRI provided excellent image quality with good MRI versus histology vessel wall thickness correlation (r=0.8). In six animals of group 2/3 MRI detected neo-intimal dissection in the abdominal aorta which was accompanied by immuno-histochemical demonstration of concomitant aforementioned novel apoptotic markers, previously implicated in the apoptotic smooth muscle cell death in vitro. CONCLUSIONS: Our studies suggest a potential role for the signal transduction pathway involving apolipoprotein C-I for in vivo apoptosis and atherosclerotic plaque rupture visualized by MRI.

Cell type-specific expression and localization of cytochrome P450 isoforms in tridimensional aggregating rat brain cell cultures.

Within the Predict-IV FP7 project a strategy for measurement of in vitro biokinetics was developed, requiring the characterization of the cellular model used, especially regarding biotransformation, which frequently depends on cytochrome P450 (CYP) activity. The extrahepatic in situ CYP-mediated metabolism is especially relevant in target organ toxicity. In this study, the constitutive mRNA levels and protein localization of different CYP isoforms were investigated in 3D aggregating brain cell cultures. CYP1A1, CYP2B1/B2, CYP2D2/4, CYP2E1 and CYP3A were expressed; CYP1A1 and 2B1 represented almost 80% of the total mRNA content. Double-immunolabeling revealed their presence in astrocytes, in neurons, and to a minor extent in oligodendrocytes, confirming the cell-specific localization of CYPs in the brain. These results together with the recently reported formation of an amiodarone metabolite following repeated exposure suggest that this cell culture system possesses some metabolic potential, most likely contributing to its high performance in neurotoxicological studies and support the use of this model in studying brain neurotoxicity involving mechanisms of toxication/detoxication.

Visual SLAM for 3D large-scale seabed acquisition employing underwater vehicles

This paper presents a novel technique to align partial 3D reconstructions of the seabed acquired by a stereo camera mounted on an autonomous underwater vehicle. Vehicle localization and seabed mapping is performed simultaneously by means of an Extended Kalman Filter. Passive landmarks are detected on the images and characterized considering 2D and 3D features. Landmarks are re-observed while the robot is navigating and data association becomes easier but robust. Once the survey is completed, vehicle trajectory is smoothed by a Rauch-Tung-Striebel filter obtaining an even better alignment of the 3D views and yet a large-scale acquisition of the seabed

Indoor Localization Solutions for a Marine Industry Augmented Reality Tool

In this report are described means for indoor localization in special, challenging circum-stances in marine industry. The work has been carried out in MARIN project, where a tool based on mobile augmented reality technologies for marine industry is developed. The tool can be used for various inspection and documentation tasks and it is aimed for improving the efficiency in design and construction work by offering the possibility to visualize the newest 3D-CAD model in real environment. Indoor localization is needed to support the system in initialization of the accurate camera pose calculation and auto-matically finding the right location in the 3D-CAD model. The suitability of each indoor localization method to the specific environment and circumstances is evaluated.

Visual SLAM for 3D large-scale seabed acquisition employing underwater vehicles

This paper presents a novel technique to align partial 3D reconstructions of the seabed acquired by a stereo camera mounted on an autonomous underwater vehicle. Vehicle localization and seabed mapping is performed simultaneously by means of an Extended Kalman Filter. Passive landmarks are detected on the images and characterized considering 2D and 3D features. Landmarks are re-observed while the robot is navigating and data association becomes easier but robust. Once the survey is completed, vehicle trajectory is smoothed by a Rauch-Tung-Striebel filter obtaining an even better alignment of the 3D views and yet a large-scale acquisition of the seabed

Caracterização in vitro de técnica biomagnética empregando magnetômetros 3D para avaliar tempo de trânsito esofagiano

The biomagnetic techniques use different magnetic field detectors to measure parameters of the human physiology. Those techniques present the advantage of being noninvasive and radiation free. Among them we can show up the Superconducting Quantum Interference Device (SQUID), the Current Alternate Biosusceptometry (ACB) and, more recently, the employment of anisotropic magnetoresistive sensors. Those magnetic sensors have a low cost and good sensitivity to measure different physiological parameters using magnetic markers. The biomagnetic techniques have being used successfully through study on the characteristics of the gastrointestinal tract. Recent research, the magnetoresistors were used to evaluate the transit time and localization of magnetic sources in different parts of the gastrointestinal tract. The objective of this work is the characterization, with in vitro tests, of a biomagnetic instrumentation using two 3-axis magnetoresistors arranged in a gradiometric coplanar setup to evaluate esophageal transit time, analyze and compare the results of experimental signals and the magnetic theory, as well as evaluate the instrumentation gain with use of tri-axial sensor front to the mono-axial sensor. The instrumentation is composed by two three-axis sensing magnetometers, precision power supply and amplifier electronic circuits. The sensors fixed in a coplanar setup were separate by distance of 18 cm. The sensitivity tests had been carried through using a cylindrical magnet (ø = 4 mm and h = 4 mm) of neodymium-iron-boron (grid 35). The tests were done moving the permanent magnet on the sensors parallel axis, simulating the food transit in... (Complete abstract click electronic access below)