scholarly journals Comparison of Tracking Techniques on 360-Degree Videos

2019 ◽  
Vol 9 (16) ◽  
pp. 3336 ◽  
Author(s):  
Tzu-Wei Mi ◽  
Mau-Tsuen Yang
Keyword(s):  
Augmented Reality ◽  
Object Tracking ◽  
Ground Truth ◽  
Physical Object ◽  
Future Research ◽  
Scale Change ◽  
Tracking Algorithms ◽  
Viewpoint Change ◽  
Pros And Cons

With the availability of 360-degree cameras, 360-degree videos have become popular recently. To attach a virtual tag on a physical object in 360-degree videos for augmented reality applications, automatic object tracking is required so the virtual tag can follow its corresponding physical object in 360-degree videos. Relative to ordinary videos, 360-degree videos in an equirectangular format have special characteristics such as viewpoint change, occlusion, deformation, lighting change, scale change, and camera shakiness. Tracking algorithms designed for ordinary videos may not work well on 360-degree videos. Therefore, we thoroughly evaluate the performance of eight modern trackers in terms of accuracy and speed on 360-degree videos. The pros and cons of these trackers on 360-degree videos are discussed. Possible improvements to adapt these trackers to 360-degree videos are also suggested. Finally, we provide a dataset containing nine 360-degree videos with ground truth of target positions as a benchmark for future research.

A Review on Automatic Bill of Material Generation and Visual Inspection on PCBs

2019 ◽  
Author(s):  
Mukhil Azhagan M. S ◽  
Dhwani Mehta ◽  
Hangwei Lu ◽  
Sudarshan Agrawal ◽  
Mark Tehranipoor ◽  
...  
Keyword(s):  
Image Analysis ◽  
Visual Inspection ◽  
Automated System ◽  
Imaging Modalities ◽  
Future Research ◽  
Analysis Techniques ◽  
Bill Of Materials ◽  
Pros And Cons ◽  
Index Terms ◽  
Image Analysis Techniques

Abstract Globalization and complexity of the PCB supply chain has made hardware assurance a challenging task. An automated system to extract the Bill of Materials (BoM) can save time and resources during the authentication process, however, there are numerous imaging modalities and image analysis techniques that can be used to create such a system. In this paper we review different imaging modalities and their pros and cons for automatic PCB inspection. In addition, image analysis techniques commonly used for such images are reviewed in a systematic way to provide a direction for future research in this area. Index Terms—Component Detection, PCB, Authentication, Image Analysis, Machine Learning

scholarly journals CIRO: The Effects of Visually Diminished Real Objects on Human Perception in Handheld Augmented Reality

Electronics ◽  
2021 ◽  
Vol 10 (8) ◽  
pp. 900
Author(s):  
Hanseob Kim ◽  
Taehyung Kim ◽  
Myungho Lee ◽  
Gerard Jounghyun Kim ◽  
Jae-In Hwang
Keyword(s):  
Augmented Reality ◽  
Real World ◽  
Human Perception ◽  
Ground Truth ◽  
Prior Work ◽  
Comparative Experiment ◽  
User Perception ◽  
Depth Distortion ◽  
Real Objects ◽  
Visual Artifacts

Augmented reality (AR) scenes often inadvertently contain real world objects that are not relevant to the main AR content, such as arbitrary passersby on the street. We refer to these real-world objects as content-irrelevant real objects (CIROs). CIROs may distract users from focusing on the AR content and bring about perceptual issues (e.g., depth distortion or physicality conflict). In a prior work, we carried out a comparative experiment investigating the effects on user perception of the AR content by the degree of the visual diminishment of such a CIRO. Our findings revealed that the diminished representation had positive impacts on human perception, such as reducing the distraction and increasing the presence of the AR objects in the real environment. However, in that work, the ground truth test was staged with perfect and artifact-free diminishment. In this work, we applied an actual real-time object diminishment algorithm on the handheld AR platform, which cannot be completely artifact-free in practice, and evaluated its performance both objectively and subjectively. We found that the imperfect diminishment and visual artifacts can negatively affect the subjective user experience.

scholarly journals Multiple Pedestrians and Vehicles Tracking in Aerial Imagery Using a Convolutional Neural Network

2021 ◽  
Vol 13 (10) ◽  
pp. 1953
Author(s):  
Seyed Majid Azimi ◽  
Maximilian Kraus ◽  
Reza Bahmanyar ◽  
Peter Reinartz
Keyword(s):  
Neural Network ◽  
Deep Learning ◽  
Convolutional Neural Network ◽  
Object Tracking ◽  
Short Term Memory ◽  
Aerial Imagery ◽  
Future Research ◽  
Short Term ◽  
Term Memory ◽  
Long Short Term Memory

In this paper, we address various challenges in multi-pedestrian and vehicle tracking in high-resolution aerial imagery by intensive evaluation of a number of traditional and Deep Learning based Single- and Multi-Object Tracking methods. We also describe our proposed Deep Learning based Multi-Object Tracking method AerialMPTNet that fuses appearance, temporal, and graphical information using a Siamese Neural Network, a Long Short-Term Memory, and a Graph Convolutional Neural Network module for more accurate and stable tracking. Moreover, we investigate the influence of the Squeeze-and-Excitation layers and Online Hard Example Mining on the performance of AerialMPTNet. To the best of our knowledge, we are the first to use these two for regression-based Multi-Object Tracking. Additionally, we studied and compared the L1 and Huber loss functions. In our experiments, we extensively evaluate AerialMPTNet on three aerial Multi-Object Tracking datasets, namely AerialMPT and KIT AIS pedestrian and vehicle datasets. Qualitative and quantitative results show that AerialMPTNet outperforms all previous methods for the pedestrian datasets and achieves competitive results for the vehicle dataset. In addition, Long Short-Term Memory and Graph Convolutional Neural Network modules enhance the tracking performance. Moreover, using Squeeze-and-Excitation and Online Hard Example Mining significantly helps for some cases while degrades the results for other cases. In addition, according to the results, L1 yields better results with respect to Huber loss for most of the scenarios. The presented results provide a deep insight into challenges and opportunities of the aerial Multi-Object Tracking domain, paving the way for future research.

Digital competences of the workforce – a research topic?

2017 ◽  
Vol 23 (3) ◽  
pp. 721-734 ◽  
Author(s):  
Matthias Murawski ◽  
Markus Bick
Keyword(s):  
Research Topic ◽  
Future Research ◽  
Digital Competence ◽  
Content Type ◽  
Research Activities ◽  
Starting Point ◽  
Pros And Cons ◽  
Definition Of ◽  
The Individual ◽  
Practical Implications

Purpose Considering working in the digital age, questions on the consequences for the individual workers are, so far, often neglected. The purpose of this paper is to deal with the question of whether the digital competences of the workforce is a research topic. The authors argue for the thesis that it is indeed a research topic. Design/methodology/approach In addition to a literature analysis of the top IS, HR, and learning publications, non-scientific sources, as well as the opinions of the authors, are included. The authors’ thesis is challenged through a debate of corresponding pros and cons. Findings The definition of digital competences lacks scientific depth. Focussing on the workforce is valid, as a “lifelong” perspective is not mandatory for research. Digital competence research is a multidisciplinary task to which the IS field can make a valuable contribution. Research limitations/implications Although relevant references are included, some aspects are mainly driven by the opinions of the authors. The theoretical implications encompass a call for a scientific definition of digital competences. Furthermore, scholars should focus on the competences of the workforce, including occupations, roles, or industries. The authors conclude by providing a first proposal of a research agenda. Practical implications The practical implications include the alignment of multiple stakeholders for the design of “digital” curricula and the integration by HR departments of the construct of digital competences, e.g. for compensation matters and job requirements. Originality/value This paper is one of very few contributions in the area of the digital competences of the workforce, and it presents a starting point for future research activities.

Research environment for developing and testing object tracking algorithms

2000 ◽  
Author(s):  
Todd Schoepflin ◽  
Christopher Lau ◽  
Rohit Garg ◽  
Donglok Kim ◽  
Yongmin Kim
Keyword(s):  
Object Tracking ◽  
Research Environment ◽  
Tracking Algorithms

CenterTrack3D: Improved CenterTrack more Suitable for 3D Objects

2021 ◽  
pp. 1-32
Author(s):  
Lipeng Gu ◽  
Shaoyuan Sun ◽  
Xunhua Liu ◽  
Xiang Li
Keyword(s):  
Object Tracking ◽  
Research Field ◽  
Unmanned Vehicles ◽  
Current Frame ◽  
3D Objects ◽  
Detection And Tracking ◽  
Tracking Algorithms ◽  
Occluded Objects ◽  
Previous Frame ◽  
3D Information

Abstract Compared with 2D multi-object tracking algorithms, 3D multi-object tracking algorithms have more research significance and broad application prospects in the unmanned vehicles research field. Aiming at the problem of 3D multi-object detection and tracking, in this paper, the multi-object tracker CenterTrack, which focuses on 2D multi-object tracking task while ignoring object 3D information, is improved mainly from two aspects of detection and tracking, and the improved network is called CenterTrack3D. In terms of detection, CenterTrack3D uses the idea of attention mechanism to optimize the way that the previous-frame image and the heatmap of previous-frame tracklets are added to the current-frame image as input, and second convolutional layer of the output head is replaced by dynamic convolution layer, which further improves the ability to detect occluded objects. In terms of tracking, a cascaded data association algorithm based on 3D Kalman filter is proposed to make full use of the 3D information of objects in the image and increase the robustness of the 3D multi-object tracker. The experimental results show that, compared with the original CenterTrack and the existing 3D multi-object tracking methods, CenterTrack3D achieves 88.75% MOTA for cars and 59.40% MOTA for pedestrians and is very competitive on the KITTI tracking benchmark test set.

Virtuelle Techniken in der Fertigung/Virtual technologies in production

2018 ◽  
Vol 108 (03) ◽  
pp. 169-173
Author(s):  
P. Brunkow ◽  
Y. Müller
Keyword(s):  
Augmented Reality ◽  
Critical Factor ◽  
Future Research ◽  
Research Needs ◽  
Innovative Techniques

Virtuelle Techniken wie Augmented Reality (AR) ermöglichen die Visualisierung virtueller Informationen wie beispielsweise Geometriedaten im selben Bild. In diesem Artikel werden Potenziale und Herausforderungen beim Einsatz von AR in der Fertigung dargestellt. Darüber hinaus wird der Mitarbeiter als kritischer Erfolgsfaktor bei der Implementierung von innovativen Techniken betrachtet und der künftige Forschungsbedarf aufgezeigt.   Virtual technologies such as Augmented Reality (AR) allow the visualization of virtual information. This article describes potentials and challenges, applying AR in production. Furthermore the employee is outlined as critical factor of success for the implementation of innovative techniques. Future research needs are pointed out.

scholarly journals Usability in 4D AR: Visualising Multi-temporal Real-time Geo-data in Augmented Reality Environments

2015 ◽  
Vol 9 (4) ◽  
pp. 23 ◽  
Author(s):  
Bernd Resch ◽  
Andreas Wichmann ◽  
Nicolas Göll
Keyword(s):  
Augmented Reality ◽  
Real Time ◽  
Temporal Variations ◽  
Time Base ◽  
Future Research ◽  
Time Data ◽  
Orientation Data ◽  
Information Density ◽  
Real Time Data ◽  
Multi Temporal

Even though advantages of 3D visualisation of multi-temporal geo-data versus 2D approaches have been widely proven, the particular pertaining challenge of real-time visualisation of geo-data in mobile Digital Earth applications has not been thoroughly tackled so far. In the emerging field of Augmented Reality (AR), research needs comprise finding the optimal information density, the interplay between orientation data in the background and other information layers, using the appropriate graphical variables for display, or selecting real-time base data with adequate quality and suitable spatial accuracy. In this paper we present a concept for integrating real-time data into 4D (three spatial dimensions plus time) AR environments, i.e., data with “high” spatial and temporal variations. We focus on three research challenges: 1.) high-performance integration of real-time data into AR; 2.) usability design in terms of displaying spatio-temporal developments and the interaction with the application; and 3.) design considerations regarding reality vs. virtuality, visualisation complexity and information density. We validated our approach in a prototypical application and extracted several limitations and future research areas including natural feature recognition, the cross-connection of (oftentimes monolithic) AR interface developments and well-established cartographic principles, or fostering the understanding of the temporal context in dynamic 4D Augmented Reality environments.

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