Evaluating tie points distribution, multiplicity and number on the accuracy of UAV photogrammetry blocks

Image orientation is a fundamental task in photogrammetric applications and it is performed by extracting keypoints with hand-crafted or learning-based methods, generating tie points among the images and running a bundle adjustment procedure. Nowadays, due to large number of extracted keypoints, tie point filtering approaches attempt to eliminate redundant tie points in order to increase accuracy and reduce processing time. This paper presents the results of an investigation concerning tie points impact on bundle adjustment results. Simulations and real data are processed in Australis and DBAT to evaluate different affecting factors, including tie point numbers, location accuracy, distribution and multiplicity. Achieved results show that increasing the amount of tie points improve the quality of bundle adjustment results, provided that the tie points are well-distributed on the image. Furthermore, bundle adjustment quality is improved as the multiplicity of tie points increases and their location uncertainty decrease. Based on simulation results, some suggestions for accurate tie points filtering in typical UAV photogrammetry blocks cases are derived

Using information content to select keypoints for UAV image matching

Image matching is one of the most important tasks in Unmanned Arial Vehicles (UAV) photogrammetry applications. The number and distribution of extracted keypoints play an essential role in the reliability and accuracy of image matching and orientation results. Conventional detectors generally produce too many redundant keypoints. In this paper, we study the effect of applying various information content criteria to keypoint selection tasks. For this reason, the quality measures of entropy, spatial saliency and texture coefficient are used to select keypoints extracted using SIFT, SURF, MSER and BRISK operators. Experiments are conducted using several synthetic and real UAV image pairs. Results show that the keypoint selection methods perform differently based on the applied detector and scene type, but in most cases, the precision of the matching results is improved by an average of 15%. In general, it can be said that applying proper keypoint selection techniques can improve the accuracy and efficiency of UAV image matching and orientation results. In addition to the evaluation, a new hybrid keypoint selection is proposed that combines all of the information content criteria discussed in this paper. This new screening method was also compared with those of SIFT, which showed 22% to 40% improvement for the bundle adjustment of UAV images

Three dimensional modelling of customer satisfaction, retention and loyalty for measuring quality of service

The aim of this thesis is to propose a model that explains the relationship between customer satisfaction, retention and loyalty based on service quality attributes. The three elements of satisfaction, retention and loyalty towards products represent ongoing challenges for the corporate financial performance. Customer behaviour analysis (known as business intelligence or customer relationship management or customer experience management) has become a major factor in the corporate decision making and strategic planning processes. Prevailing logic dictates that by improving service attributes one should expect better customer satisfaction levels. Consequently, improved satisfaction levels should increase the probability of customer retention and degree of loyalty. Substantial research work has been dedicated to explain the importance of customer behaviour measurement for industry. However, there is little evidence that there has been an overall integrating empirical research that relates the three elements of satisfaction, retention and loyalty with respect to service quality attributes. Empirical data collected from the UK mobile telecommunication for this research shows that such an objective model that is capable of capturing this three dimensional relationship will contribute towards more robust decision making and better strategic planning. The proposed thesis extracts the data about key service attributes from a combination of literature review, surveys, and interviews from the UK mobile telecommunication industry. Responses were analysed using multiple regression, regression analysis with dummy variables, logistic regression, logistic regression with dummy variables and structural equation modelling (SEM) to test variables and their interrelationships. This study makes a step forward and contributes to the body of knowledge as it: (a) highlights the role of service attribute performance towards customer satisfaction, consequently identifies attributes that affect satisfaction and dissatisfaction of customers, (b) maps the relationship between attribute importance and attribute performance, (c) optimise resource allocation process using importance-performance analysis (IPA), (d) classifies customers with respect to the role and length of relationship they have with the company (switching probability), and (e) describes the interrelationship between customer satisfaction, retention and loyalty. The novelty of the research lies in: (a) establishment of a framework that links service attribute performance to customer satisfaction and then to customer future intentions (customer retention and customer loyalty), and (b) provision of a model that could assist key decision makers in prudent usage of resources for maximum profitability. This dissertation presents a novel approach methodology and modelling construct for customer behaviour analysis. For proof of concept it presents a case study in the mobile telecommunication industry. It is worth noting that in this research work Customer Retention is interpreted as probability of switching between service providers. Customer Loyalty is interpreted as referral (word-of-mouth) activity by existing customers.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

A new multi-criteria tie point filtering approach to increase the accuracy of UAV photogrammetry models

Extracting accurate tie points plays an essential role in the accuracy of image orientation in Unmanned Aerial Vehicle (UAV) photogrammetry. In this study, a Multi-Criteria Decision Making (MCDM) automatic filtering method is presented. Based on the quality features of a photogrammetric model, the proposed method works at the level of sparse point cloud to remove low-quality tie points for refining the orientation results. In the proposed algorithm, different factors that affect the quality of tie points are identified. The quality measures are then aggregated by applying MCDM methods and a competency score for each 3D tie point. These scores are employed in an automatic filtering approach that selects a subset of high-quality points which are then used to repeat the bundle adjustment. To evaluate the proposed algorithm, various internal and external studies were conducted on different datasets. The findings suggest that our method is both effective and reliable. In addition, in comparison to the existing filtering techniques, the proposed strategy increases the accuracy of bundle adjustment and dense point cloud generation by about 40% and 70%, respectively

Comparison of Lumbopelvic and Hip Movement Patterns During Passive Hip External Rotation in Two Groups of Low Back Pain Patients with and without Rotational Demand Activities.

BACKGROUND Because different groups of people with low back pain (LBP) engage in different tasks, their lumbopelvic-hip complex may move in different ways in those groups. The purpose of this study was to quantify the differences in lumbopelvic movement pattern during the passive hip external rotation (PHER) test in LBP patients with and without rotational demand activities (RDA). MATERIAL AND METHODS A total of 30 subjects with LBP, including 15 patients with-RDA and 15 patients without-RDA were enrolled. A passive hip external rotation test was performed. Pelvic and hip rotation over the full range of the test, timing of hip and pelvic motion, and pelvic rotation in the first half of the movement were measured using a 3-D motion analysis system. RESULTS Passive pelvic rotation during the test in the group with RDA was significantly greater than in the other group. However, there was no significant difference between the groups in other kinematic variables, including hip external rotation, timing of hip and pelvic motion and pelvic rotation in the first half of the movement (p > 0.05). CONCLUSIONS 1. A greater lumbopelvic rotation ROM during the PHER existed in LBP patients who regularly participated in RDA. 2. Different groups of patients with LBP who engage in different specific activities may have a specific lumbopelvic movement pattern impairment. Therefore, each group of LBP patients in regard to their specific activities may need a different, specific plan of treatment

Investigating the effects of strategic positioning for development of modern banking services

During the past few years, there have been tremendous changes on banking services and many bank customers are able to do their daily banking activities using recent advances of technology such as internet banking, telephone banking, etc. In this paper, we present an empirical investigation on the effects of strategic positioning for development of modern banking services. The proposed study designs a questionnaire in Likert scale and distributes it among some 385 randomly selected people who live in Tehran in 2013. The questionnaire consists of seven factors including property positioning, advantage positioning, consumer positioning, user positioning, competitive advantage positioning, quality positioning and merchandise category positioning. Using Spearman correlation as well as stepwise regression technique, the study has determined positive and meaningful relationships between different components of strategy positioning development of modern banking services

The Diagnostic Value of Anthropometric Characteristics of Ilium for Sex Estimation Using Pelvic Radiographs

Background: Sex estimation is an essential part of forensic identification. This study was conducted on the Iranian people to determine pelvic bones anthropometric characteristics.Methods: Radiography of 180 pelvic bones (90 males and 90 females) was studied. We measured the height of ilium, inter-acetabular distance, acetabular diameter, the greatest breadth of the pelvis, breadth of pelvic inlet, and the presence of the beaklike bony extension in both sexes.Results: We found a significant difference between men and women regarding their mean height of ilium, acetabular diameter, inter-acetabular distance, breadth of the pelvic inlet in all studied X-rays. The highest accuracy for sex estimation was related to the height of ilium (77%). The prevalence of the beaklike bony extension was 43% in the studied population, 70% in males and 18% in females.Conclusion: When human skeletal remains containing pelvic bones are available, standard radiographic images along with other findings can be helpful in predicting the sex.