Multirow Boundary-Labeling Algorithms for Panorama Images

2015 ◽  
Vol 1 (1) ◽  
pp. 1-30 ◽  
Author(s):  
Andreas Gemsa ◽  
Jan-Henrik Haunert ◽  
Martin Nöllenburg
Keyword(s):  
Labeling Algorithms ◽  
Boundary Labeling

Addressing pose estimation issues for machine vision based UAV autonomous serial refuelling

2007 ◽  
Vol 111 (1120) ◽  
pp. 389-396 ◽  
Author(s):  
G. Campa ◽  
M. R. Napolitano ◽  
M. Perhinschi ◽  
M. L. Fravolini ◽  
L. Pollini ◽  
...  
Keyword(s):  
Machine Vision ◽  
Pose Estimation ◽  
Estimation Algorithm ◽  
Computational Effort ◽  
Unmanned Aircraft ◽  
Light Sources ◽  
Estimation Algorithms ◽  
Trade Offs ◽  
Labeling Algorithms ◽  
Selection Of

Abstract This paper describes the results of an effort on the analysis of the performance of specific ‘pose estimation’ algorithms within a Machine Vision-based approach for the problem of aerial refuelling for unmanned aerial vehicles. The approach assumes the availability of a camera on the unmanned aircraft for acquiring images of the refuelling tanker; also, it assumes that a number of active or passive light sources – the ‘markers’ – are installed at specific known locations on the tanker. A sequence of machine vision algorithms on the on-board computer of the unmanned aircraft is tasked with the processing of the images of the tanker. Specifically, detection and labeling algorithms are used to detect and identify the markers and a ‘pose estimation’ algorithm is used to estimate the relative position and orientation between the two aircraft. Detailed closed-loop simulation studies have been performed to compare the performance of two ‘pose estimation’ algorithms within a simulation environment that was specifically developed for the study of aerial refuelling problems. Special emphasis is placed on the analysis of the required computational effort as well as on the accuracy and the error propagation characteristics of the two methods. The general trade offs involved in the selection of the pose estimation algorithm are discussed. Finally, simulation results are presented and analysed.

On the readability of leaders in boundary labeling

2018 ◽  
Vol 18 (1) ◽  
pp. 110-132
Author(s):  
Lukas Barth ◽  
Andreas Gemsa ◽  
Benjamin Niedermann ◽  
Martin Nöllenburg
Keyword(s):  
Detailed Analysis ◽  
Task Performance ◽  
User Study ◽  
Point Of View ◽  
Practical Point ◽  
Subjective Preference ◽  
Two Measures ◽  
Preference Ratings ◽  
Boundary Labeling

External labeling deals with annotating features in images with labels that are placed outside of the image and are connected by curves (so-called leaders) to the corresponding features. While external labeling has been extensively investigated from a perspective of automatization, the research on its readability has been neglected. In this article, we present the first formal user study on the readability of leader types in boundary labeling, a special variant of external labeling that considers rectangular image contours. We consider the four most studied leader types (straight, L-shaped, diagonal, and S-shaped) with respect to their performance, that is, whether and how fast a viewer can assign a feature to its label and vice versa. We give a detailed analysis of the results regarding the readability of the four models and discuss their aesthetic qualities based on the users’ preference judgments and interviews. As a consequence of our experiment, we can generally recommend L-shaped leaders as the best compromise between measured task performance and subjective preference ratings, while straight and diagonal leaders received mixed ratings in the two measures. S-shaped leaders are generally not recommended from a practical point of view.

scholarly journals Boundary labeling: Models and efficient algorithms for rectangular maps

2007 ◽  
Vol 36 (3) ◽  
pp. 215-236 ◽  
Author(s):  
Michael A. Bekos ◽  
Michael Kaufmann ◽  
Antonios Symvonis ◽  
Alexander Wolff
Keyword(s):  
Efficient Algorithms ◽  
Boundary Labeling

One-and-a-Half-Side Boundary Labeling

2011 ◽  
pp. 387-398 ◽  
Author(s):  
Chun-Cheng Lin ◽  
Sheung-Hung Poon ◽  
Shigeo Takahashi ◽  
Hsiang-Yun Wu ◽  
Hsu-Chun Yen
Keyword(s):  
Boundary Labeling

Multi-stack Boundary Labeling Problems

2006 ◽  
pp. 81-92 ◽  
Author(s):  
Michael A. Bekos ◽  
Michael Kaufmann ◽  
Katerina Potika ◽  
Antonios Symvonis
Keyword(s):  
Boundary Labeling

Vertex-labeling algorithms for the Hilbert spacefilling curve

2001 ◽  
Vol 31 (5) ◽  
pp. 395-408 ◽  
Author(s):  
John J. Bartholdi ◽  
Paul Goldsman
Keyword(s):  
Labeling Algorithms

scholarly journals Temporal structure of mouse courtship vocalizations facilitates syllable labeling

2020 ◽  
Vol 3 (1) ◽  
Author(s):  
Stav Hertz ◽  
Benjamin Weiner ◽  
Nisim Perets ◽  
Michael London
Keyword(s):  
Neural Control ◽  
Temporal Order ◽  
Temporal Structure ◽  
Ultrasonic Vocalizations ◽  
Sequence Structure ◽  
Information Maximization ◽  
Information Score ◽  
Labeling Algorithms ◽  
Structure Improvement

AbstractMice emit sequences of ultrasonic vocalizations (USVs) but little is known about the rules governing their temporal order and no consensus exists on the classification of USVs into syllables. To address these questions, we recorded USVs during male-female courtship and found a significant temporal structure. We labeled USVs using three popular algorithms and found that there was no one-to-one relationships between their labels. As label assignment affects the high order temporal structure, we developed the Syntax Information Score (based on information theory) to rank labeling algorithms based on how well they predict the next syllable in a sequence. Finally, we derived a novel algorithm (Syntax Information Maximization) that utilizes sequence statistics to improve the clustering of individual USVs with respect to the underlying sequence structure. Improvement in USV classification is crucial for understanding neural control of vocalization. We demonstrate that USV syntax holds valuable information towards achieving this goal.

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