Strain and strain rate by two-dimensional speckle tracking echocardiography in a maned wolf

The measurement of cardiovascular features of wild animals is important, as is the measurement in pets, for the assessment of myocardial function and the early detection of cardiac abnormalities, which could progress to heart failure. Speckle tracking echocardiography (2D STE) is a new tool that has been used in veterinary medicine, which demonstrates several advantages, such as angle independence and the possibility to provide the early diagnosis of myocardial alterations. The aim of this study was to evaluate the left myocardial function in a maned wolf by 2D STE. Thus, the longitudinal, circumferential and radial strain and strain rate were obtained, as well as, the radial and longitudinal velocity and displacement values, from the right parasternal long axis four-chamber view, the left parasternal apical four chamber view and the parasternal short axis at the level of the papillary muscles. The results of the longitudinal variables were -13.52±7.88, -1.60±1.05, 4.34±2.52 and 3.86±3.04 for strain (%), strain rate (1/s), displacement (mm) and velocity (cm/s), respectively. In addition, the radial and circumferential Strain and Strain rate were 24.39±14.23, 1.86±0.95 and -13.69±6.53, -1.01±0.48, respectively. Thus, the present study provides the first data regarding the use of this tool in maned wolves, allowing a more complete quantification of myocardial function in this species.

Rocket tracking and decoupling eigenstructure control law

A control law was designed for a satellite launcher ( rocket ) vehicle using eigenstructure assignment in order that the vehicle tracks a reference attitude and also to decouple the yaw response from roll and pitch manoeuvres and to decouple the pitch response from roll and yaw manoeuvres. The design was based on a complete linear coupled model obtained from the complete vehicle non linear model by linearization at each trajectory point. After all, the design was assessed with the vehicle time varying non-linear model showing a good performance and robustness. The used design method is explained and a case study for the Brazilian satellite launcher ( VLS Rocket ) is reported.

Real-time Image-based RGB-D Camera Motion Tracking and Environment Mapping

In this work, image based estimation methods, also known as direct methods, are studied which avoid feature extraction and matching completely. Cost functions use raw pixels as measurements and the goal is to produce precise 3D pose and structure estimates. The cost functions presented minimize the sensor error, because measurements are not transformed or modified. In photometric camera pose estimation, 3D rotation and translation parameters are estimated by minimizing a sequence of image based cost functions, which are non-linear due to perspective projection and lens distortion. In image based structure refinement, on the other hand, 3D structure is refined using a number of additional views and an image based cost metric. Image based estimation methods are particularly useful in conditions where the Lambertian assumption holds, and the 3D points have constant color despite viewing angle. The goal is to improve image based estimation methods, and to produce computationally efficient methods which can be accomodated into real-time applications. The developed image-based 3D pose and structure estimation methods are finally demonstrated in practise in indoor 3D reconstruction use, and in a live augmented reality application.

Hand tracking in high-speed camera videos

Visual object tracking has been one of the most popular research topics in the field of computer vision recently. Specifically, hand tracking has attracted significant attention since it would enable many useful practical applications. However, hand tracking is still a very challenging problem which cannot be considered solved. The fact that almost every aspect of hand appearance can change is the fundamental reason for this difficulty. This thesis focused on 2D-based hand tracking in high-speed camera videos. During the project, a toolbox for this purpose was collected which contains nine different tracking methods. In the experiments, these methods were tested and compared against each other with both high-speed videos recorded during the project and publicly available normal speed videos. The results revealed that tracking accuracies varied considerably depending on the video and the method. Therefore, no single method was clearly the best in all videos, but three methods, CT, HT, and TLD, performed better than the others overall. Moreover, the results provide insights about the suitability of each method to different types and situations of hand tracking.

Model-Based Tracking Initialization in Ship Building Environment

An augmented reality (AR) device must know observer’s location and orientation, i.e. observer’s pose, to be able to correctly register the virtual content to observer’s view. One possible way to determine and continuously follow-up the pose is model-based visual tracking. It supposes that a 3D model of the surroundings is known and that there is a video camera that is fixed to the device. The pose is tracked by comparing the video camera image to the model. Each new pose estimate is usually based on the previous estimate. However, the first estimate must be found out without a prior estimate, i.e. the tracking must be initialized, which in practice means that some model features must be identified from the image and matched to model features. This is known in literature as model-to-image registration problem or simultaneous pose and correspondence problem. This report reviews visual tracking initialization methods that are suitable for visual tracking in ship building environment when the ship CAD model is available. The environment is complex, which makes the initialization non-trivial. The report has been done as part of MARIN project.

Aircraft tracking and classification with vhf passive bistatic radar

Since the times preceding the Second World War the subject of aircraft tracking has been a core interest to both military and non-military aviation. During subsequent years both technology and configuration of the radars allowed the users to deploy it in numerous fields, such as over-the-horizon radar, ballistic missile early warning systems or forward scatter fences. The latter one was arranged in a bistatic configuration. The bistatic radar has continuously re-emerged over the last eighty years for its intriguing capabilities and challenging configuration and formulation. The bistatic radar arrangement is used as the basis of all the analyzes presented in this work. The aircraft tracking method of VHF Doppler-only information, developed in the first part of this study, is solely based on Doppler frequency readings in relation to time instances of their appearance. The corresponding inverse problem is solved by utilising a multistatic radar scenario with two receivers and one transmitter and using their frequency readings as a base for aircraft trajectory estimation. The quality of the resulting trajectory is then compared with ground-truth information based on ADS-B data. The second part of the study deals with the developement of a method for instantaneous Doppler curve extraction from within a VHF time-frequency representation of the transmitted signal, with a three receivers and one transmitter configuration, based on a priori knowledge of the probability density function of the first order derivative of the Doppler shift, and on a system of blocks for identifying, classifying and predicting the Doppler signal. The extraction capabilities of this set-up are tested with a recorded TV signal and simulated synthetic spectrograms. Further analyzes are devoted to more comprehensive testing of the capabilities of the extraction method. Besides testing the method, the classification of aircraft is performed on the extracted Bistatic Radar Cross Section profiles and the correlation between them for different types of aircraft. In order to properly estimate the profiles, the ADS-B aircraft location information is adjusted based on extracted Doppler frequency and then used for Bistatic Radar Cross Section estimation. The classification is based on seven types of aircraft grouped by their size into three classes.

Hardware Accelarated Visual Tracking Algorithms. A Systematic Literature Review

Many industrial applications need object recognition and tracking capabilities. The algorithms developed for those purposes are computationally expensive. Yet ,real time performance, high accuracy and small power consumption are essential measures of the system. When all these requirements are combined, hardware acceleration of these algorithms becomes a feasible solution. The purpose of this study is to analyze the current state of these hardware acceleration solutions, which algorithms have been implemented in hardware and what modifications have been done in order to adapt these algorithms to hardware.

Recent advances in monocular model-based tracking: a systematic literature review

In this paper, we review the advances of monocular model-based tracking for last ten years period until 2014. In 2005, Lepetit, et. al, [19] reviewed the status of monocular model based rigid body tracking. Since then, direct 3D tracking has become quite popular research area, but monocular model-based tracking should still not be forgotten. We mainly focus on tracking, which could be applied to aug- mented reality, but also some other applications are covered. Given the wide subject area this paper tries to give a broad view on the research that has been conducted, giving the reader an introduction to the different disciplines that are tightly related to model-based tracking. The work has been conducted by searching through well known academic search databases in a systematic manner, and by selecting certain publications for closer examination. We analyze the results by dividing the found papers into different categories by their way of implementation. The issues which have not yet been solved are discussed. We also discuss on emerging model-based methods such as fusing different types of features and region-based pose estimation which could show the way for future research in this subject.

Optical and photoelectric properties of dry bacteriorhodopsin sensors

In this thesis, bacteriorhodopsin (BR) photosensor’s optical and electrical properties were studied. The BR sensor consisted of a dry film with BR in polyvinyl alcohol and covered with transparent conductors. In the experiments the BR photocycle was started with two lasers. The characteristics of the BR sensor were measured in two ways. The first approach was theoretical and it required knowing the laser parameters. The second way required assembling a measurement setup for the optical response measurements. However, no measurable results were obtained due to low laser power. The photoelectric response was measured in the experiments with two laser systems and the amplifier was tested. In the experiment with a Cavitar laser, the photoelectric response was obtained. In the experiment with FemtoFiber Pro laser, the photoelectric response was not measured. The expected amplitude of the response was obtained. The experimental data was analyzed and possible solutions for reducing the interference were given.

Exploring the impact of celebrity endorsement and product class involvement on advertising effectiveness: an eye tracking approach

Celebrity endorsement has increased in popularity over the past decades and companies are willing to spend increasingly excessive amounts of money into it. Even though multiple studies support celebrity endorsement, further research on its impact on advertising effectiveness is called for. Fur-ther, the role of consumers’ product class involvement in advertising needs to be further studied. The purpose of this study is to explore if consumers’ product class involvement and exposure to celebrity endorsers affect consumers brand recall. Supported by earlier studies, brand recall was used as a measure for advertising effectiveness in this study. In general, a psychological approach was chosen for building the theoretical framework. Concept of classical conditioning was presented in order to understand why people act how they do. Balanced theory and meaning transfer model were presented in order to study how celebrities can be used effectively in advertising context. Further, the importance of product class involvement in advertising effectiveness was evaluated. Hypotheses were formulated based on a literature review of the existing research. Because of the versatility of the research design, a mixed methods approach for this study was adopted. Empirical part of the study was conducted in three stages. First, a pre-test was conducted in order to choose suitable product endorsers for the advertisement stimuli used in the experiment. Second, an eye-tracking experiment with 30 test subjects was conducted in order to study how people view advertisements and whether the familiarity of the product endorser and consumers’ product class involvement affects brand recall. For the experiment, a fictional brand was created in order to avoid bias on brand recall. Third, qualitative interviews for 15 test subjects were conducted in the post-experiment stage in order to gain deeper understating of the phenomenon and to make sense of the findings from the experiment. Findings from this study support celebrity endorsement by suggesting that a famous spokesperson does not steal attention from brand information more than a non-celebrity product endorser. As a result, the use of a celebrity endorser did not decrease brand recall. Results support earlier research as consumer’ higher product class involvement resulted in a better brand recall. Findings from the interviews suggest that consumers have positive perceptions of celebrity endorsement in general. However, the celebrity–brand congruence is a crucial factor when creating attitudes towards the advertisement. Future research ideas were presented based on the limitations and results of this study

Tracking tendencias en cámaras de comercio del mundo 2012: Análisis de tendencias en servicios por parte de entidades que desarrollan servicios similares a la CCB en el mundo

Banco del conocimiento

The influence of drug-induced dyskinesias on manual tracking in Parkinson's disease

The influence of peak-dose drug-induced dyskinesia (DID) on manual tracking (MT) was examined in 10 dyskinetic patients (OPO), and compared to 10 age/gendermatched non-dyskinetic patients (NDPD) and 10 healthy controls. Whole body movement (WBM) and MT were recorded with a 6-degrees of freedom magnetic motion tracker and forearm rotation sensors, respectively. Subjects were asked to match the length of a computer-generated line with a line controlled via wrist rotation. Results show that OPO patients had greater WBM displacement and velocity than other groups. All groups displayed increased WBM from rest to MT, but only DPD and NDPO patients demonstrated a significant increase in WBM displacement and velocity. In addition, OPO patients exhibited excessive increase in WBM suggesting overflow DID. When two distinct target pace segments were examined (FAST/SLOW), all groups had slight increases in WBM displacement and velocity from SLOW to FAST, but only OPO patients showed significantly increased WBM displacement and velocity from SLOW to FAST. Therefore, it can be suggested that overflow DID was further increased with increased task speed. OPO patients also showed significantly greater ERROR matching target velocity, but no significant difference in ERROR in displacement, indicating that significantly greater WBM displacement in the OPO group did not have a direct influence on tracking performance. Individual target and performance traces demonstrated this relatively good tracking performance with the exception of distinct deviations from the target trace that occurred suddenly, followed by quick returns to the target coherent in time with increased performance velocity. In addition, performance hand velocity was not correlated with WBM velocity in DPO patients, suggesting that increased ERROR in velocity was not a direct result of WBM velocity. In conclusion, we propose that over-excitation of motor cortical areas, reported to be present in DPO patients, resulted in overflow DID during voluntary movement. Furthermore, we propose that the increased ERROR in velocity was the result of hypermetric voluntary movements also originating from the over-excitation of motor cortical areas.

Real-Time Automatic Object Classification and Tracking using Genetic Programming and NVIDIA R CUDA TM

Genetic Programming (GP) is a widely used methodology for solving various computational problems. GP's problem solving ability is usually hindered by its long execution times. In this thesis, GP is applied toward real-time computer vision. In particular, object classification and tracking using a parallel GP system is discussed. First, a study of suitable GP languages for object classification is presented. Two main GP approaches for visual pattern classification, namely the block-classifiers and the pixel-classifiers, were studied. Results showed that the pixel-classifiers generally performed better. Using these results, a suitable language was selected for the real-time implementation. Synthetic video data was used in the experiments. The goal of the experiments was to evolve a unique classifier for each texture pattern that existed in the video. The experiments revealed that the system was capable of correctly tracking the textures in the video. The performance of the system was on-par with real-time requirements.

Characterizing Dynamic Optimization Benchmarks for the Comparison of Multi-Modal Tracking Algorithms

Population-based metaheuristics, such as particle swarm optimization (PSO), have been employed to solve many real-world optimization problems. Although it is of- ten sufficient to find a single solution to these problems, there does exist those cases where identifying multiple, diverse solutions can be beneficial or even required. Some of these problems are further complicated by a change in their objective function over time. This type of optimization is referred to as dynamic, multi-modal optimization. Algorithms which exploit multiple optima in a search space are identified as niching algorithms. Although numerous dynamic, niching algorithms have been developed, their performance is often measured solely on their ability to find a single, global optimum. Furthermore, the comparisons often use synthetic benchmarks whose landscape characteristics are generally limited and unknown. This thesis provides a landscape analysis of the dynamic benchmark functions commonly developed for multi-modal optimization. The benchmark analysis results reveal that the mechanisms responsible for dynamism in the current dynamic bench- marks do not significantly affect landscape features, thus suggesting a lack of representation for problems whose landscape features vary over time. This analysis is used in a comparison of current niching algorithms to identify the effects that specific landscape features have on niching performance. Two performance metrics are proposed to measure both the scalability and accuracy of the niching algorithms. The algorithm comparison results demonstrate the algorithms best suited for a variety of dynamic environments. This comparison also examines each of the algorithms in terms of their niching behaviours and analyzing the range and trade-off between scalability and accuracy when tuning the algorithms respective parameters. These results contribute to the understanding of current niching techniques as well as the problem features that ultimately dictate their success.