People favour imperfect catching by assuming a stable world

The visual angle that is projected by an object (e.g. a ball) on the retina depends on the object's size and distance. Without further information, however, the visual angle is ambiguous with respect to size and distance, because equal visual angles can be obtained from a big ball at a longer distance and a smaller one at a correspondingly shorter distance. Failure to recover the true 3D structure of the object (e.g. a ball's physical size) causing the ambiguous retinal image can lead to a timing error when catching the ball. Two opposing views are currently prevailing on how people resolve this ambiguity when estimating time to contact. One explanation challenges any inference about what causes the retinal image (i.e. the necessity to recover this 3D structure), and instead favors a direct analysis of optic flow. In contrast, the second view suggests that action timing could be rather based on obtaining an estimate of the 3D structure of the scene. With the latter, systematic errors will be predicted if our inference of the 3D structure fails to reveal the underlying cause of the retinal image. Here we show that hand closure in catching virtual balls is triggered by visual angle, using an assumption of a constant ball size. As a consequence of this assumption, hand closure starts when the ball is at similar distance across trials. From that distance on, the remaining arrival time, therefore, depends on ball's speed. In order to time the catch successfully, closing time was coupled with ball's speed during the motor phase. This strategy led to an increased precision in catching but at the cost of committing systematic errors.

Most and Least Preferred Colours Differ According to Object Context : New Insights from an Unrestricted Colour Range

Humans like some colours and dislike others, but which particular colours and why remains to be understood. Empirical studies on colour preferences generally targeted most preferred colours, but rarely least preferred (disliked) colours. In addition, findings are often based on general colour preferences leaving open the question whether results generalise to specific objects. Here, 88 participants selected the colours they preferred most and least for three context conditions (general, interior walls, t-shirt) using a high-precision colour picker. Participants also indicated whether they associated their colour choice to a valenced object or concept. The chosen colours varied widely between individuals and contexts and so did the reasons for their choices. Consistent patterns also emerged, as most preferred colours in general were more chromatic, while for walls they were lighter and for t-shirts they were darker and less chromatic compared to least preferred colours. This meant that general colour preferences could not explain object specific colour preferences. Measures of the selection process further revealed that, compared to most preferred colours, least preferred colours were chosen more quickly and were less often linked to valenced objects or concepts. The high intra- and inter-individual variability in this and previous reports furthers our understanding that colour preferences are determined by subjective experiences and that most and least preferred colours are not processed equally.

Diagnostic performance of 3D TSE MRI versus 2D TSE MRI of the knee at 1.5 T, with prompt arthroscopic correlation, in the detection of meniscal and cruciate ligament tears

Abstract Objective: To compare the diagnostic performance of the three-dimensional turbo spin-echo (3D TSE) magnetic resonance imaging (MRI) technique with the performance of the standard two-dimensional turbo spin-echo (2D TSE) protocol at 1.5 T, in the detection of meniscal and ligament tears. Materials and Methods: Thirty-eight patients were imaged twice, first with a standard multiplanar 2D TSE MR technique, and then with a 3D TSE technique, both in the same 1.5 T MRI scanner. The patients underwent knee arthroscopy within the first three days after the MRI. Using arthroscopy as the reference standard, we determined the diagnostic performance and agreement. Results: For detecting anterior cruciate ligament tears, the 3D TSE and routine 2D TSE techniques showed similar values for sensitivity (93% and 93%, respectively) and specificity (80% and 85%, respectively). For detecting medial meniscal tears, the two techniques also had similar sensitivity (85% and 83%, respectively) and specificity (68% and 71%, respectively). In addition, for detecting lateral meniscal tears, the two techniques had similar sensitivity (58% and 54%, respectively) and specificity (82% and 92%, respectively). There was a substantial to almost perfect intraobserver and interobserver agreement when comparing the readings for both techniques. Conclusion: The 3D TSE technique has a diagnostic performance similar to that of the routine 2D TSE protocol for detecting meniscal and anterior cruciate ligament tears at 1.5 T, with the advantage of faster acquisition.

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

Using appearance and context for outdoor scene object classification

We propose a probabilistic object classifier for outdoor scene analysis as a first step in solving the problem of scene context generation. The method begins with a top-down control, which uses the previously learned models (appearance and absolute location) to obtain an initial pixel-level classification. This information provides us the core of objects, which is used to acquire a more accurate object model. Therefore, their growing by specific active regions allows us to obtain an accurate recognition of known regions. Next, a stage of general segmentation provides the segmentation of unknown regions by a bottom-strategy. Finally, the last stage tries to perform a region fusion of known and unknown segmented objects. The result is both a segmentation of the image and a recognition of each segment as a given object class or as an unknown segmented object. Furthermore, experimental results are shown and evaluated to prove the validity of our proposal

Java 3D

Tämä insinöörityö kertoo Java 3D -ohjelmointirajapinnan perusteista ja sen käytöstä kolmiulotteisen tietokonegrafiikan luomisessa Java ohjelmointikielellä. Java 3D on rajapinta Java-ohjelmointikielelle, jonka avulla voidaan luoda ja käsitellä kolmiulotteista tietokonegrafiikkaa. Java 3D -rajapinnan avulla käsitellään kolmiulotteista tietokonegrafiikka erityisen maisemagraafimallin avulla. Maisemagraafi on binääripuuta muistuttava malli, joka mahdollistaa kolmiulotteisten kohteiden ja niille tapahtuvien muunnoksien käsittelyn hierarkisessa järjestyksessä. Työssä käydään läpi Java 3D -maisemagraafien luominen ja kolmiulotteisessa avaruudessa sijaitseville kappaleille tehtäviä perusoperaatioita kuten siirtoa ja kiertoa. Lisäksi käydään läpi myös erilaisia animoinnissa ja interaktiossa käytettäviä luokkia, joiden avulla ohjelmoija saa automatisoitua muunnoksia sekä käyttäjä voi antaa syötteitä hiirellä ja näppäimistöllä. Näiden lisäksi käydään läpi myös mallin valaistusta, varjoja, teksturointia sekä omien kolmiulotteisten mallien tuontia Java 3D -maailmaan. Opinnäytetyön yhteydessä on tehty myös kirjo erilaisia esimerkkejä, jotka ovat saatavilla verkkosivustolta osoitteessa http://www.pahvilaatikko.org/j3d lisäksi kopio verkkosivustosta löytyy myös opinnäytetyön mukana tulevalta cd-levyltä.

Computing the persistent homology of range images with alpha shapes

Laser scanning is becoming an increasingly popular method for measuring 3D objects in industrial design. Laser scanners produce a cloud of 3D points. For CAD software to be able to use such data, however, this point cloud needs to be turned into a vector format. A popular way to do this is to triangulate the assumed surface of the point cloud using alpha shapes. Alpha shapes start from the convex hull of the point cloud and gradually refine it towards the true surface of the object. Often it is nontrivial to decide when to stop this refinement. One criterion for this is to do so when the homology of the object stops changing. This is known as the persistent homology of the object. The goal of this thesis is to develop a way to compute the homology of a given point cloud when processed with alpha shapes, and to infer from it when the persistent homology has been achieved. Practically, the computation of such a characteristic of the target might be applied to power line tower span analysis.

Performance and Methodological Aspects in Positron Emission Tomography

Performance standards for Positron emission tomography (PET) were developed to be able to compare systems from different generations and manufacturers. This resulted in the NEMA methodology in North America and the IEC in Europe. In practices, the NEMA NU 2- 2001 is the method of choice today. These standardized methods allow assessment of the physical performance of new commercial dedicated PET/CT tomographs. The point spread in image formation is one of the factors that blur the image. The phenomenon is often called the partial volume effect. Several methods for correcting for partial volume are under research but no real agreement exists on how to solve it. The influence of the effect varies in different clinical settings and it is likely that new methods are needed to solve this problem. Most of the clinical PET work is done in the field of oncology. The whole body PET combined with a CT is the standard investigation today in oncology. Despite the progress in PET imaging technique visualization, especially quantification of small lesions is a challenge. In addition to partial volume, the movement of the object is a significant source of error. The main causes of movement are respiratory and cardiac motions. Most of the new commercial scanners are in addition to cardiac gating, also capable of respiratory gating and this technique has been used in patients with cancer of the thoracic region and patients being studied for the planning of radiation therapy. For routine cardiac applications such as assessment of viability and perfusion only cardiac gating has been used. However, the new targets such as plaque or molecular imaging of new therapies require better control of the cardiac motion also caused by respiratory motion. To overcome these problems in cardiac work, a dual gating approach has been proposed. In this study we investigated the physical performance of a new whole body PET/CT scanner with NEMA standard, compared methods for partial volume correction in PET studies of the brain and developed and tested a new robust method for dual cardiac-respiratory gated PET with phantom, animal and human data. Results from performance measurements showed the feasibility of the new scanner design in 2D and 3D whole body studies. Partial volume was corrected, but there is no best method among those tested as the correction also depends on the radiotracer and its distribution. New methods need to be developed for proper correction. The dual gating algorithm generated is shown to handle dual-gated data, preserving quantification and clearly eliminating the majority of contraction and respiration movement

Unsupervised visual object categorization

The number of digital images has been increasing exponentially in the last few years. People have problems managing their image collections and finding a specific image. An automatic image categorization system could help them to manage images and find specific images. In this thesis, an unsupervised visual object categorization system was implemented to categorize a set of unknown images. The system is unsupervised, and hence, it does not need known images to train the system which needs to be manually obtained. Therefore, the number of possible categories and images can be huge. The system implemented in the thesis extracts local features from the images. These local features are used to build a codebook. The local features and the codebook are then used to generate a feature vector for an image. Images are categorized based on the feature vectors. The system is able to categorize any given set of images based on the visual appearance of the images. Images that have similar image regions are grouped together in the same category. Thus, for example, images which contain cars are assigned to the same cluster. The unsupervised visual object categorization system can be used in many situations, e.g., in an Internet search engine. The system can categorize images for a user, and the user can then easily find a specific type of image.

3D Surface Modeling From Point Clouds

The goal of this thesis is to implement software for creating 3D models from point clouds. Point clouds are acquired with stereo cameras, monocular systems or laser scanners. The created 3D models are triangular models or NURBS (Non-Uniform Rational B-Splines) models. Triangular models are constructed from selected areas from the point clouds and resulted triangular models are translated into a set of quads. The quads are further translated into an estimated grid structure and used for NURBS surface approximation. Finally, we have a set of NURBS surfaces which represent the whole model. The problem wasn’t so easy to solve. The selected triangular surface reconstruction algorithm did not deal well with noise in point clouds. To handle this problem, a clustering method is introduced for simplificating the model and removing noise. As we had better results with the smaller point clouds produced by clustering, we used points in clusters to better estimate the grids for NURBS models. The overall results were good when the point cloud did not have much noise. The point clouds with small amount of error had good results as the triangular model was solid. NURBS surface reconstruction performed well on solid models.

Um novo modelo para os sítios de interação dos antagonistas H2, baseado na caracterização química dos sítios primário e secundário por QSAR- 3D

A new model for the H2 antagonists binding site is postulated based on adsorption coefficient values of sixteen antagonists, in the affinities constants of the primary and secondary binding sites, and in the chemical characterization of these sites by 3D-QSAR. All study compounds are in the extended conformation and deprotonated form. The lateral validation of the QSARs, CoMFA analysis, affinity constants and chemical similarity data suggest that the antagonists block the proton pump in the H2 receptor interacting with two tyrosines - one in the helix 5, and other in the helix 6.

Simulations of 3D Stripixel Detectors

Large Hadron Collider (LHC) is the main particle accelerator at CERN. LHC is created with main goal to search elementary particles and help science investigate our universe. Radiation in LHC is caused by charged particles circular acceleration, therefore detectors tracing particles in existed severe conditions during the experiments must be radiation tolerant. Moreover, further upgrade of luminosity (up to 1035 cm-2s-1) requires development of particle detector’s structure. This work is dedicated to show the new type 3D stripixel detector with serious structural improvement. The new type of radiation-hard detector has a three-dimensional (3D) array of the p+ and n+ electrodes that penetrate into the detector bulk. The electrons and holes are then collected at oppositely biased electrodes. Proposed 3D stripixel detector demonstrates that full depletion voltage is lower that that for planar detectors. Low depletion voltage is one of the main advantages because only depleted part of the device is active are. Because of small spacing between electrodes, charge collection distances are smaller which results in high speed of the detector’s response. In this work is also briefly discussed dual-column type detectors, meaning consisting both n+ and p+ type columnar electrodes in its structure, and was declared that dual-column detectors show better electric filed distribution then single sided radiation detectors. The dead space or in other words low electric field region in significantly suppressed. Simulations were carried out by using Atlas device simulation software. As a simulation results in this work are represented the electric field distribution under different bias voltages.

Modelling syntectonic sedimentation: combining a discrete element model of tectonic. Deformation and process-based sedimentary Model in 3D.

This paper presents a new numerical program able to model syntectonic sedimentation. The new model combines a discrete element model of the tectonic deformation of a sedimentary cover and a process-based model of sedimentation in a single framework. The integration of these two methods allows us to include the simulation of both sedimentation and deformation processes in a single and more effective model. The paper describes briefly the antecedents of the program, Simsafadim-Clastic and a discrete element model, in order to introduce the methodology used to merge both programs to create the new code. To illustrate the operation and application of the program, analysis of the evolution of syntectonic geometries in an extensional environment and also associated with thrust fault propagation is undertaken. Using the new code, much more complex and realistic depositional structures can be simulated together with a more complex analysis of the evolution of the deformation within the sedimentary cover, which is seen to be affected by the presence of the new syntectonic sediments.

Estudos de QSAR 3D para um conjunto de inibidores de butirilcolinesterase humana

Alzheimer's disease (AD) is considered the main cause of cognitive decline in adults. The available therapies for AD treatment seek to maintain the activity of cholinergic system through the inhibition of the enzyme acetylcholinesterase. However, butyrylcholinesterase (BuChE) can be considered an alternative target for AD treatment. Aiming at developing new BuChE inhibitors, robust QSAR 3D models with high predictive power were developed. The best model presents a good fit (r²=0.82, q²=0.76, with two PCs) and high predictive power (r²predict=0.88). Analysis of regression vector shows that steric properties have considerable importance to the inhibition of the BuChE.