Parallel coordinates in computational engineering design

Modern Engineering Design involves the deployment of many computational tools. Re- search on challenging real-world design problems is focused on developing improvements for the engineering design process through the integration and application of advanced com- putational search/optimization and analysis tools. Successful application of these methods generates vast quantities of data on potential optimum designs. To gain maximum value from the optimization process, designers need to visualise and interpret this information leading to better understanding of the complex and multimodal relations between param- eters, objectives and decision-making of multiple and strongly conflicting criteria. Initial work by the authors has identified that the Parallel Coordinates interactive visualisation method has considerable potential in this regard. This methodology involves significant levels of user-interaction, making the engineering designer central to the process, rather than the passive recipient of a deluge of pre-formatted information. In the present work we have applied and demonstrated this methodology in two differ- ent aerodynamic turbomachinery design cases; a detailed 3D shape design for compressor blades, and a preliminary mean-line design for the whole compressor core. The first case comprises 26 design parameters for the parameterisation of the blade geometry, and we analysed the data produced from a three-objective optimization study, thus describing a design space with 29 dimensions. The latter case comprises 45 design parameters and two objective functions, hence developing a design space with 47 dimensions. In both cases the dimensionality can be managed quite easily in Parallel Coordinates space, and most importantly, we are able to identify interesting and crucial aspects of the relationships between the design parameters and optimum level of the objective functions under con- sideration. These findings guide the human designer to find answers to questions that could not even be addressed before. In this way, understanding the design leads to more intelligent decision-making and design space exploration. © 2012 AIAA.

Structure from Stereo and Motion

Stereopsis and motion parallax are two methods for recovering three dimensional shape. Theoretical analyses of each method show that neither alone can recover rigid 3D shapes correctly unless other information, such as perspective, is included. The solutions for recovering rigid structure from motion have a reflection ambiguity; the depth scale of the stereoscopic solution will not be known unless the fixation distance is specified in units of interpupil separation. (Hence the configuration will appear distorted.) However, the correct configuration and the disposition of a rigid 3D shape can be recovered if stereopsis and motion are integrated, for then a unique solution follows from a set of linear equations. The correct interpretation requires only three points and two stereo views.

Parameter Sensitive Detectors

Object detection can be challenging when the object class exhibits large variations. One commonly-used strategy is to first partition the space of possible object variations and then train separate classifiers for each portion. However, with continuous spaces the partitions tend to be arbitrary since there are no natural boundaries (for example, consider the continuous range of human body poses). In this paper, a new formulation is proposed, where the detectors themselves are associated with continuous parameters, and reside in a parameterized function space. There are two advantages of this strategy. First, a-priori partitioning of the parameter space is not needed; the detectors themselves are in a parameterized space. Second, the underlying parameters for object variations can be learned from training data in an unsupervised manner. In profile face detection experiments, at a fixed false alarm number of 90, our method attains a detection rate of 75% vs. 70% for the method of Viola-Jones. In hand shape detection, at a false positive rate of 0.1%, our method achieves a detection rate of 99.5% vs. 98% for partition based methods. In pedestrian detection, our method reduces the miss detection rate by a factor of three at a false positive rate of 1%, compared with the method of Dalal-Triggs.

Learning a Family of Detectors

Object detection and recognition are important problems in computer vision. The challenges of these problems come from the presence of noise, background clutter, large within class variations of the object class and limited training data. In addition, the computational complexity in the recognition process is also a concern in practice. In this thesis, we propose one approach to handle the problem of detecting an object class that exhibits large within-class variations, and a second approach to speed up the classification processes. In the first approach, we show that foreground-background classification (detection) and within-class classification of the foreground class (pose estimation) can be jointly solved with using a multiplicative form of two kernel functions. One kernel measures similarity for foreground-background classification. The other kernel accounts for latent factors that control within-class variation and implicitly enables feature sharing among foreground training samples. For applications where explicit parameterization of the within-class states is unavailable, a nonparametric formulation of the kernel can be constructed with a proper foreground distance/similarity measure. Detector training is accomplished via standard Support Vector Machine learning. The resulting detectors are tuned to specific variations in the foreground class. They also serve to evaluate hypotheses of the foreground state. When the image masks for foreground objects are provided in training, the detectors can also produce object segmentation. Methods for generating a representative sample set of detectors are proposed that can enable efficient detection and tracking. In addition, because individual detectors verify hypotheses of foreground state, they can also be incorporated in a tracking-by-detection frame work to recover foreground state in image sequences. To run the detectors efficiently at the online stage, an input-sensitive speedup strategy is proposed to select the most relevant detectors quickly. The proposed approach is tested on data sets of human hands, vehicles and human faces. On all data sets, the proposed approach achieves improved detection accuracy over the best competing approaches. In the second part of the thesis, we formulate a filter-and-refine scheme to speed up recognition processes. The binary outputs of the weak classifiers in a boosted detector are used to identify a small number of candidate foreground state hypotheses quickly via Hamming distance or weighted Hamming distance. The approach is evaluated in three applications: face recognition on the face recognition grand challenge version 2 data set, hand shape detection and parameter estimation on a hand data set, and vehicle detection and estimation of the view angle on a multi-pose vehicle data set. On all data sets, our approach is at least five times faster than simply evaluating all foreground state hypotheses with virtually no loss in classification accuracy.

Optical and mechanical analysis on a biological cell in optical tweezers

La réponse mécanique d’une cellule à une force externe permet d’inférer sa structure et fonction. Les pinces optiques s’avèrent une approche particulièrement attrayante pour la manipulation et caractérisation biophysique sophistiquée des cellules de façon non invasive. Cette thèse explore l’utilisation de trois types de pinces optiques couramment utilisées : 1) statiques (static), 2) à exposition partagée (time-sharing) et 3) oscillantes (oscillating). L’utilisation d’un code basé sur la méthode des éléments finis en trois dimensions (3DFEM) nous permet de modéliser ces trois types de piégeage optique afin d’extraire les propriétés mécaniques cellulaires à partir des expériences. La combinaison des pinces optiques avec la mécanique des cellules requiert des compétences interdisciplinaires. Une revue des approches expérimentales sur le piégeage optique et les tests unicellulaires est présentée. Les bases théoriques liant l’interaction entre la force radiative optique et la réponse mécanique de la cellule aussi. Pour la première fois, une simulation adaptée (3DFEM) incluant la diffusion lumineuse et la distribution du stress radiatif permet de prédire la déformation d’une cellule biconcave –analogue aux globules rouges—dans un piège statique double (static dual-trap). À l’équilibre, on observe que la déformation finale est donnée par l’espacement entre les deux faisceaux lasers: la cellule peut être étirée ou même comprimée. L’exposition partagée (time-sharing) est la technique qui permet de maintenir plusieurs sites de piégeage simultanément à partir du même faisceau laser. Notre analyse quantitative montre que, même oscillantes, la force optique et la déformation sont omniprésentes dans la cellule : la déformation viscoélastique et la dissipation de l’énergie sont analysées. Une autre cellule-type, la tige cubique, est étudiée : cela nous permet d’élucider de nouvelles propriétés sur la symétrie de la réponse mécanique. Enfin, l’analyse de la déformation résolue en temps dans un piége statique ou à exposition partagée montre que la déformation dépend simultanément de la viscoélasticité, la force externe et sa forme tridimensionnelle. La technique à force oscillante (oscillating tweezers) montre toutefois un décalage temporel, entre la force et la déformation, indépendant de la forme 3D; cette approche donnerait directement accès au tenseur viscoélastique complexe de la cellule.

Articulated Model Registration of MRI/X-Ray Spine Data

This paper presents a method based on articulated models for the registration of spine data extracted from multimodal medical images of patients with scoliosis. With the ultimate aim being the development of a complete geometrical model of the torso of a scoliotic patient, this work presents a method for the registration of vertebral column data using 3D magnetic resonance images (MRI) acquired in prone position and X-ray data acquired in standing position for five patients with scoliosis. The 3D shape of the vertebrae is estimated from both image modalities for each patient, and an articulated model is used in order to calculate intervertebral transformations required in order to align the vertebrae between both postures. Euclidean distances between anatomical landmarks are calculated in order to assess multimodal registration error. Results show a decrease in the Euclidean distance using the proposed method compared to rigid registration and more physically realistic vertebrae deformations compared to thin-plate-spline (TPS) registration thus improving alignment.

Recovering Euclidean deformable models from stereo-motion

In this paper we present a novel structure from motion (SfM) approach able to infer 3D deformable models from uncalibrated stereo images. Using a stereo setup dramatically improves the 3D model estimation when the observed 3D shape is mostly deforming without undergoing strong rigid motion. Our approach first calibrates the stereo system automatically and then computes a single metric rigid structure for each frame. Afterwards, these 3D shapes are aligned to a reference view using a RANSAC method in order to compute the mean shape of the object and to select the subset of points on the object which have remained rigid throughout the sequence without deforming. The selected rigid points are then used to compute frame-wise shape registration and to extract the motion parameters robustly from frame to frame. Finally, all this information is used in a global optimization stage with bundle adjustment which allows to refine the frame-wise initial solution and also to recover the non-rigid 3D model. We show results on synthetic and real data that prove the performance of the proposed method even when there is no rigid motion in the original sequence

Convex Hulls in Image Processing : A Scoping Review

The demands of image processing related systems are robustness, high recognition rates, capability to handle incomplete digital information, and magnanimous flexibility in capturing shape of an object in an image. It is exactly here that, the role of convex hulls comes to play. The objective of this paper is twofold. First, we summarize the state of the art in computational convex hull development for researchers interested in using convex hull image processing to build their intuition, or generate nontrivial models. Secondly, we present several applications involving convex hulls in image processing related tasks. By this, we have striven to show researchers the rich and varied set of applications they can contribute to. This paper also makes a humble effort to enthuse prospective researchers in this area. We hope that the resulting awareness will result in new advances for specific image recognition applications.

Underwater mapping using sonar

[ES]El proyecto contiene módulos de simulación, procesado de datos, mapeo y localización, desarrollados en C++ utilizando ROS (Robot Operating System) y PCL (Point Cloud Library). Ha sido desarrollado bajo el proyecto de robótica submarina AVORA.Se han caracterizado el vehículo y el sensor, y se han analizado diferentes tecnologías de sensores y mapeo. Los datos pasan por tres etapas: Conversión a nube de puntos, filtrado por umbral, eliminación de puntos espureos y, opcionalmente, detección de formas. Estos datos son utilizados para construir un mapa de superficie multinivel. La otra herramienta desarrollada es un algoritmo de Punto más Cercano Iterativo (ICP) modificado, que tiene en cuenta el modo de funcionamiento del sonar de imagen utilizado.

PS-GANS: A Patient-Specific, Gravity Assisted Navigation System for Acetabular Cup Placement

In this paper we propose a new system that allows reliable acetabular cup placement when the THA is operated in lateral approach. Conceptually it combines the accuracy of computer-generated patient-specific morphology information with an easy-to-use mechanical guide, which effectively uses natural gravity as the angular reference. The former is achieved by using a statistical shape model-based 2D-3D reconstruction technique that can generate a scaled, patient-specific 3D shape model of the pelvis from a single conventional anteroposterior (AP) pelvic X-ray radiograph. The reconstructed 3D shape model facilitates a reliable and accurate co-registration of the mechanical guide with the patient’s anatomy in the operating theater. We validated the accuracy of our system by conducting experiments on placing seven cups to four pelvises with different morphologies. Taking the measurements from an image-free navigation system as the ground truth, our system showed an average accuracy of 2.1 ±0.7 o for inclination and an average accuracy of 1.2 ±1.4 o for anteversion.

Computer Vision-Based Carbohydrate Estimation for Type 1 Diabetic Patients Using Smartphones

Background: Individuals with type 1 diabetes (T1D) have to count the carbohydrates (CHOs) of their meal to estimate the prandial insulin dose needed to compensate for the meal’s effect on blood glucose levels. CHO counting is very challenging but also crucial, since an error of 20 grams can substantially impair postprandial control. Method: The GoCARB system is a smartphone application designed to support T1D patients with CHO counting of nonpacked foods. In a typical scenario, the user places a reference card next to the dish and acquires 2 images with his/her smartphone. From these images, the plate is detected and the different food items on the plate are automatically segmented and recognized, while their 3D shape is reconstructed. Finally, the food volumes are calculated and the CHO content is estimated by combining the previous results and using the USDA nutritional database. Results: To evaluate the proposed system, a set of 24 multi-food dishes was used. For each dish, 3 pairs of images were taken and for each pair, the system was applied 4 times. The mean absolute percentage error in CHO estimation was 10 ± 12%, which led to a mean absolute error of 6 ± 8 CHO grams for normal-sized dishes. Conclusion: The laboratory experiments demonstrated the feasibility of the GoCARB prototype system since the error was below the initial goal of 20 grams. However, further improvements and evaluation are needed prior launching a system able to meet the inter- and intracultural eating habits.

GoCARB: Smartphone-App zur Kohlenhydratberechnung bei Typ-1-Diabetes

Smartphone-App zur Kohlenhydratberechnung Neue Technologien wie Blutzuckersensoren und moderne Insulinpumpen prägten die Therapie des Typ-1-Diabetes (T1D) in den letzten Jahren in wesentlichem Ausmaß. Smartphones sind aufgrund ihrer rasanten technischen Entwicklung eine weitere Plattform für Applikationen zur Therapieunterstützung bei T1D. GoCARB Hierbei handelt es sich um ein zur Kohlenhydratberechnung entwickeltes System für Personen mit T1D. Die Basis für Endanwender stellt ein Smartphone mit Kamera dar. Zur Berechnung werden 2 mit dem Smartphone aus verschiedenen Winkeln aufgenommene Fotografien einer auf einem Teller angerichteten Mahlzeit benötigt. Zusätzlich ist eine neben dem Teller platzierte Referenzkarte erforderlich. Die Grundlage für die Kohlenhydratberechnung ist ein Computer-Vision-gestütztes Programm, das die Mahlzeiten aufgrund ihrer Farbe und Textur erkennt. Das Volumen der Mahlzeit wird mit Hilfe eines dreidimensional errechneten Modells bestimmt. Durch das Erkennen der Art der Mahlzeiten sowie deren Volumen kann GoCARB den Kohlenhydratanteil unter Einbeziehung von Nährwerttabellen berechnen. Für die Entwicklung des Systems wurde eine Bilddatenbank von mehr als 5000 Mahlzeiten erstellt und genutzt. Resümee Das GoCARB-System befindet sich aktuell in klinischer Evaluierung und ist noch nicht für Patienten verfügbar.

Geomorphology and spectrophotometry of Philae's landing site on comet 67P/Churyumov-Gerasimenko

Context. On 12 November 2014 the European mission Rosetta succeeded in delivering a lander, named Philae, on the surface of one of the smallest, low-gravity and most primitive bodies of the solar system, the comet 67P/Churyumov-Gerasimenko (67P). Aims. The aim of this paper is to provide a comprehensive geomorphological and spectrophotometric analysis of Philae's landing site (Agilkia) to give an essential framework for the interpretation of its in situ measurements. Methods. OSIRIS images, coupled with gravitational slopes derived from the 3D shape model based on stereo-photogrammetry were used to interpret the geomorphology of the site. We adopted the Hapke model, using previously derived parameters, to photometrically correct the images in orange filter (649.2 nm). The best approximation to the Hapke model, given by the Akimov parameter-less function, was used to correct the reflectance for the effects of viewing and illumination conditions in the other filters. Spectral analyses on coregistered color cubes were used to retrieve spectrophotometric properties. Results. The landing site shows an average normal albedo of 6.7% in the orange filter with variations of similar to 15% and a global featureless spectrum with an average red spectral slope of 15.2%/100 nm between 480.7 nm (blue filter) and 882.1 nm (near-IR filter). The spatial analysis shows a well-established correlation between the geomorphological units and the photometric characteristics of the surface. In particular, smooth deposits have the highest reflectance a bluer spectrum than the outcropping material across the area. Conclusions. The featureless spectrum and the redness of the material are compatible with the results by other instruments that have suggested an organic composition. The observed small spectral variegation could be due to grain size effects. However, the combination of photometric and spectral variegation suggests that a compositional differentiation is more likely. This might be tentatively interpreted as the effect of the efficient dust-transport processes acting on 67P. High-activity regions might be the original sources for smooth fine-grained materials that then covered Agilkia as a consequence of airfall of residual material. More observations performed by OSIRIS as the comet approaches the Sun would help interpreting the processes that work at shaping the landing site and the overall nucleus.

Carbohydrate Estimation by a Mobile Phone-Based System Versus Self-Estimations of Individuals With Type 1 Diabetes Mellitus: A Comparative Study

Background: Diabetes mellitus is spreading throughout the world and diabetic individuals have been shown to often assess their food intake inaccurately; therefore, it is a matter of urgency to develop automated diet assessment tools. The recent availability of mobile phones with enhanced capabilities, together with the advances in computer vision, have permitted the development of image analysis apps for the automated assessment of meals. GoCARB is a mobile phone-based system designed to support individuals with type 1 diabetes during daily carbohydrate estimation. In a typical scenario, the user places a reference card next to the dish and acquires two images using a mobile phone. A series of computer vision modules detect the plate and automatically segment and recognize the different food items, while their 3D shape is reconstructed. Finally, the carbohydrate content is calculated by combining the volume of each food item with the nutritional information provided by the USDA Nutrient Database for Standard Reference. Objective: The main objective of this study is to assess the accuracy of the GoCARB prototype when used by individuals with type 1 diabetes and to compare it to their own performance in carbohydrate counting. In addition, the user experience and usability of the system is evaluated by questionnaires. Methods: The study was conducted at the Bern University Hospital, “Inselspital” (Bern, Switzerland) and involved 19 adult volunteers with type 1 diabetes, each participating once. Each study day, a total of six meals of broad diversity were taken from the hospital’s restaurant and presented to the participants. The food items were weighed on a standard balance and the true amount of carbohydrate was calculated from the USDA nutrient database. Participants were asked to count the carbohydrate content of each meal independently and then by using GoCARB. At the end of each session, a questionnaire was completed to assess the user’s experience with GoCARB. Results: The mean absolute error was 27.89 (SD 38.20) grams of carbohydrate for the estimation of participants, whereas the corresponding value for the GoCARB system was 12.28 (SD 9.56) grams of carbohydrate, which was a significantly better performance ( P=.001). In 75.4% (86/114) of the meals, the GoCARB automatic segmentation was successful and 85.1% (291/342) of individual food items were successfully recognized. Most participants found GoCARB easy to use. Conclusions: This study indicates that the system is able to estimate, on average, the carbohydrate content of meals with higher accuracy than individuals with type 1 diabetes can. The participants thought the app was useful and easy to use. GoCARB seems to be a well-accepted supportive mHealth tool for the assessment of served-on-a-plate meals.

Molecular and isotopic properties of gases from ODP Holes of ODP Leg 204

We report and discuss molecular and isotopic properties of hydrate-bound gases from 55 samples and void gases from 494 samples collected during Ocean Drilling Program (ODP) Leg 204 at Hydrate Ridge offshore Oregon. Gas hydrates appear to crystallize in sediments from two end-member gas sources (deep allochthonous and in situ) as mixtures of different proportions. In an area of high gas flux at the Southern Summit of the ridge (Sites 1248-1250), shallow (0-40 m below the seafloor [mbsf]) gas hydrates are composed of mainly allochthonous mixed microbial and thermogenic methane and a small portion of thermogenic C2+ gases, which migrated vertically and laterally from as deep as 2- to 2.5-km depths. In contrast, deep (50-105 mbsf) gas hydrates at the Southern Summit (Sites 1248 and 1250) and on the flanks of the ridge (Sites 1244-1247) crystallize mainly from microbial methane and ethane generated dominantly in situ. A small contribution of allochthonous gas may also be present at sites where geologic and tectonic settings favor focused vertical gas migration from greater depth (e.g., Sites 1244 and 1245). Non-hydrocarbon gases such as CO2 and H2S are not abundant in sampled hydrates. The new gas geochemical data are inconsistent with earlier models suggesting that seafloor gas hydrates at Hydrate Ridge formed from gas derived from decomposition of deeper and older gas hydrates. Gas hydrate formation at the Southern Summit is explained by a model in which gas migrated from deep sediments, and perhaps was trapped by a gas hydrate seal at the base of the gas hydrate stability zone (GHSZ). Free gas migrated into the GHSZ when the overpressure in gas column exceeded sealing capacity of overlaying sediments, and precipitated as gas hydrate mainly within shallow sediments. The mushroom-like 3D shape of gas hydrate accumulation at the summit is possibly defined by the gas diffusion aureole surrounding the main migration conduit, the decrease of gas solubility in shallow sediment, and refocusing of gas by carbonate and gas hydrate seals near the seafloor to the crest of the local anticline structure.