IDENTIFICATION AND MATCHING OF PLANES IN A PAIR OF UNCALIBRATED IMAGES

2003 ◽  
Vol 17 (07) ◽  
pp. 1127-1143 ◽  
Author(s):  
B. S. BOUFAMA ◽  
D. J. O'CONNELL
Keyword(s):  
Prior Knowledge ◽  
Seed Region ◽  
Uncalibrated Images ◽  
Dense Matching ◽  
Key Points ◽  
Current Region ◽  
Correlation Techniques ◽  
Surface Discontinuity ◽  
And Performance ◽  
Plane Homography

In this paper, we propose a new method to simultaneously achieve segmentation and dense matching in a pair of stereo images. In contrast to conventional methods that are based on similarity or correlation techniques, this method is based on geometry, and uses correlations only on a limited number of key points. Stemming from the observation that our environment is abundant in planes, this method focuses on segmentation and matching of planes in an observed scene. Neither prior knowledge about the scene nor camera calibration are needed. Using two uncalibrated images as inputs, the method starts with a rough identification of a potential plane, defined by three points only. Based on these three points, a plane homography is then calculated and, used for validation. Starting from a seed region defined by the original three points, the method grows the current region by successive move/confirmation steps until occlusions and/or surface discontinuity occur. In this case, the homography-based mapping of points between the two images will not be valid anymore. This condition is detected by the correlation, used in the confirmation process. In particular, this method grows a region even across different colors as long as the region is planar. Experiments on real images validated our method and showed its capability and performance.

scholarly journals True-orthophoto generation from UAV images: Implementation of a combined photogrammetric and computer vision approach

2014 ◽  
Vol II-5 ◽  
pp. 57-63 ◽  
Author(s):  
L. Barazzetti ◽  
R. Brumana ◽  
D. Oreni ◽  
M. Previtali ◽  
F. Roncoroni
Keyword(s):  
3D Model ◽  
Bundle Block Adjustment ◽  
Dense Matching ◽  
Automated Data Processing ◽  
Feature Based ◽  
Correlation Techniques ◽  
Uav Images ◽  
Image Orientation ◽  
Santa Maria

This paper presents a photogrammetric methodology for true-orthophoto generation with images acquired from UAV platforms. The method is an automated multistep workflow made up of three main parts: (i) image orientation through feature-based matching and collinearity equations / bundle block adjustment, (ii) dense matching with correlation techniques able to manage multiple images, and true-orthophoto mapping for 3D model texturing. It allows automated data processing of sparse blocks of convergent images in order to obtain a final true-orthophoto where problems such as self-occlusions, ghost effects, and multiple texture assignments are taken into consideration. <br><br> The different algorithms are illustrated and discussed along with a real case study concerning the UAV flight over the Basilica di Santa Maria di Collemaggio in L'Aquila (Italy). The final result is a rigorous true-orthophoto used to inspect the roof of the Basilica, which was seriously damaged by the earthquake in 2009.

Introduction

2021 ◽  
pp. xviii-22
Author(s):  
Milija Gluhovic ◽  
Silvija Jestrovic ◽  
Shirin Rai ◽  
Michael Saward
Keyword(s):  
Performance Studies ◽  
Interdisciplinary Approach ◽  
First Century ◽  
Field Of Study ◽  
Political World ◽  
Key Points ◽  
Challenges And Opportunities ◽  
And Performance ◽  
Key Terms ◽  
A Current

Beginning with two vivid examples that illustrate the Handbook’s core arguments—that politics is performative, performance is political, and that both of these matter to understanding our worlds—the introduction provides a current, contextual account of the shared syntax of politics and performance. It defines key terms, such as politics, performance, theatricality, and performativity, that inform the Handbook contributions. Through accessible and provocative engagements with new ways of thinking about politics and performance in both disciplinary and interdisciplinary modes, the introduction shows that these categories are interwoven and entangled in complex and consequential ways. It outlines the states of the art in theater and performance studies and politics, respectively, capturing key points of interconnection between these discourses in order to build on, extend, and reshape interdisciplinary conversations. Finally, it reflects on key challenges and opportunities that attend bringing the two broad fields together for mutual enrichment and building a new, hybrid field of study. Underlining the co-constitutive nature of performance and politics, the introduction suggests that such a framework is critical to promoting an interdisciplinary approach to understanding the complex political world of the twenty-first century.

The Association Between Prior Knowledge and Learning Approaches, in Performance in an Advanced Accounting Course

2015 ◽  
Vol 21 (4) ◽  
pp. 922-925
Author(s):  
Nor Azah Binti Abdul Jalil ◽  
Hasnah Binti Haron
Keyword(s):  
Prior Knowledge ◽  
Study Skills ◽  
Approaches To Learning ◽  
Accounting Education ◽  
Significant Variable ◽  
Learning Approaches ◽  
Contributing Factors ◽  
Course Performance ◽  
And Performance ◽  
And Gender

Ensuring quality in accounting education is the target by academicians in the field. One of the measures would be students’ performance which would be the benchmark of indicating whether the students are performing accordingly. Based on previous literature, prior knowledge and students’ learning approaches are seen as contributing factors to performance. The purpose of this study is to determine the following: (1) to identify whether the students with prior knowledge perform better in an advanced accounting course, (2) to identify whether learning approaches (deep, surface and strategic) could also contribute to students’ performances and (3) to identify association between gender and performance. A total of 109 students responded to the questionnaires consisting Approaches and Study Skills Inventory for Students (ASSIST) which was used to identify the approaches to learning adopted by IIUM students. The results found that prior knowledge is the only significant variable and there is no association found between learning approaches and gender towards advanced accounting course performance. It implies that more effort should be directed at increasing the students’ comprehension in the prior knowledge which would include increase student centre learning approaches in teaching.

“Charm the Air to Give a Sound”

2013 ◽  
pp. 190-213
Author(s):  
Amy Herzog
Keyword(s):  
New York ◽  
Digital Media ◽  
Role Playing ◽  
Careful Examination ◽  
Historical Texts ◽  
Digital Era ◽  
Key Points ◽  
Sound Environment ◽  
And Performance ◽  
The Individual

This article appears in the Oxford Handbook of Sound and Image in Digital Media edited by Carol Vernallis, Amy Herzog, and John Richardson. This essay examines the soundscape and architecture of Punchdrunk’s immersive theater installation Sleep No More (New York, 2011). Although many of its sonic references are drawn from well-known analog sources, their deployment marks a shift in the role of sound in theater and film. The installation’s sound environment establishes ambience and also guides and synchronizes the actions of the individual audience- and cast members who navigate the space during each performance. The use of sonic cues, in this context, draws directly from the logic of role-playing video games. Moreover, the use of rhythm and repetition in Sleep No More resonates on an even deeper register with similar architectures of meaning in some of the work’s key points of reference. A careful examination the work’s structure reveals a complex deployment of sonic patterning that activates new connections with historical texts and challenges our understanding of the experience of sound, touch, and performance in the digital era.

Rewards and Penalties

Gamification ◽  
2015 ◽  
pp. 1003-1014 ◽  
Author(s):  
Hope Caton ◽  
Darrel Greenhill
Keyword(s):  
Student Performance ◽  
Computer Game ◽  
Quantitative Evidence ◽  
Team Projects ◽  
Student Teams ◽  
Key Points ◽  
Daily Attendance ◽  
And Performance ◽  
Computing Module ◽  
Assessment Strategies

This paper describes how a gamified rewards and penalties framework was used to increase attendance and engagement in a level six undergraduate computing module teaching game production. The framework was applied to the same module over two consecutive years: a control year and a trial year. In both years the tutor, assignments and assessment strategies were the same and daily attendance was recorded. In the module, students work in multi-disciplinary teams to complete an assignment to build a computer game prototype. Unequal contribution to team projects by other students is a frequently voiced complaint to lecturers setting team assignments: a problem which is only partially solved by peer assessments, which are a retrospective analysis. The gamification framework provides a method for the lecturer to quickly identify disengaging students and to re-motivate them. Partnership between student and teacher, both parties must present themselves in order for that exchange of knowledge to take place. If unequal team contribution is a constant problem for students, then empty lecture halls can be considered similarly difficult for educators. This paper addresses three key points: 1) Does the rewards/penalties framework improve attendance? 2) If yes, does improved attendance result in improved assessments? 3) Does the framework improve engagement and performance in student teams? This paper presents quantitative evidence to answer the first two and offers speculative comments on the third. Initial results suggest that the rewards and penalties framework improves attendance and increases student performance and overall grade. Speculatively, the framework appears to be effective in increasing motivation. Informal student commentary indicates that while motivation is not improved across the cohort, those that are motivated contribute significantly more time and effort to the project. Rewards proved successful in improving completion of previously resisted tasks and in attracting students to attend classes they would otherwise miss.

scholarly journals Deep learning–assisted prostate cancer detection on bi-parametric MRI: minimum training data size requirements and effect of prior knowledge

2021 ◽  
Author(s):  
Matin Hosseinzadeh ◽  
Anindo Saha ◽  
Patrick Brand ◽  
Ilse Slootweg ◽  
Maarten de Rooij ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Deep Learning ◽  
Prior Knowledge ◽  
Training Data ◽  
Expert Performance ◽  
Free Response ◽  
Algorithm Performance ◽  
Prostate Imaging ◽  
Key Points ◽  
Clinically Significant

Abstract Objectives To assess Prostate Imaging Reporting and Data System (PI-RADS)–trained deep learning (DL) algorithm performance and to investigate the effect of data size and prior knowledge on the detection of clinically significant prostate cancer (csPCa) in biopsy-naïve men with a suspicion of PCa. Methods Multi-institution data included 2734 consecutive biopsy-naïve men with elevated PSA levels (≥ 3 ng/mL) that underwent multi-parametric MRI (mpMRI). mpMRI exams were prospectively reported using PI-RADS v2 by expert radiologists. A DL framework was designed and trained on center 1 data (n = 1952) to predict PI-RADS ≥ 4 (n = 1092) lesions from bi-parametric MRI (bpMRI). Experiments included varying the number of cases and the use of automatic zonal segmentation as a DL prior. Independent center 2 cases (n = 296) that included pathology outcome (systematic and MRI targeted biopsy) were used to compute performance for radiologists and DL. The performance of detecting PI-RADS 4–5 and Gleason > 6 lesions was assessed on 782 unseen cases (486 center 1, 296 center 2) using free-response ROC (FROC) and ROC analysis. Results The DL sensitivity for detecting PI-RADS ≥ 4 lesions was 87% (193/223, 95% CI: 82–91) at an average of 1 false positive (FP) per patient, and an AUC of 0.88 (95% CI: 0.84–0.91). The DL sensitivity for the detection of Gleason > 6 lesions was 85% (79/93, 95% CI: 77–83) @ 1 FP compared to 91% (85/93, 95% CI: 84–96) @ 0.3 FP for a consensus panel of expert radiologists. Data size and prior zonal knowledge significantly affected performance (4%, $$p<0.05$$ p < 0.05 ). Conclusion PI-RADS-trained DL can accurately detect and localize Gleason > 6 lesions. DL could reach expert performance using substantially more than 2000 training cases, and DL zonal segmentation. Key Points • AI for prostate MRI analysis depends strongly on data size and prior zonal knowledge. • AI needs substantially more than 2000 training cases to achieve expert performance.

scholarly journals The Effect of Logistics Salience on Logistical Capabilities and Firm Performances

2020 ◽  
Vol 5 (1) ◽  
Author(s):  
Muhammad Furqan Rahim ◽  
Muhammad Asim ◽  
Salman Manzoor
Keyword(s):  
Supply Chain ◽  
Positive Impact ◽  
Service Differentiation ◽  
Supply Chain Integration ◽  
Survey Method ◽  
Data Collection And Analysis ◽  
Correlation Techniques ◽  
And Performance ◽  
Highly Correlated ◽  
Logistics Capabilities

The purpose of the study is to evaluate the effect of logistics salience on logistics capabilities and performance. The two selected capabilities in the study are service differentiation and innovation. much of the literature has focused on the development of logistics through being customer focused, managing supply chain, integration of processes, measurement and exchanging information therefore, attention shall also be provided on some other and less talked about logistical capabilities which includes innovation and differentiation. The study used survey method for data collection and analysis. The sample size of the study is 150 regression and correlation techniques were applied on the data using SPSS. It was obtained from the results that logistics salience has a positive impact on logistic capabilities and performance. Furthermore, the study also found that logistics innovativeness and service differentiation goes hand in hand and are highly correlated.

Introduction

2017 ◽  
Author(s):  
Gordon L. Clark ◽  
Ashby H. B. Monk
Keyword(s):  
Financial Markets ◽  
Institutional Investors ◽  
Financial Risk ◽  
Service Providers ◽  
Investment Strategies ◽  
Risk And Uncertainty ◽  
Key Points ◽  
Investment Returns ◽  
And Performance

It is acknowledged that institutional investors underpin the structure and performance of global financial markets. There is no doubt that the growth of institutional investors over the past fifty years has given global financial markets a remarkable depth of liquidity and scope of activities. At the same time, institutional investors rely on financial markets to frame and implement their investment strategies. Therefore, it is important to understand what is distinctive about this environment compared with those of other industries, especially manufacturing. In Chapter 1, the authors explain the significance of financial risk and uncertainty in the production of investment returns from a viewpoint of what could be termed a map of financial risk and uncertainty. The role and significance of institutional investors, including asset owners, managers and service providers, is highlighted. Concluding Chapter 1 is a summary of key points for the following chapters in the book.

Sign in / Sign up

Export Citation Format

Share Document