Robust and real-time pose tracking for augmented reality on mobile devices

2017 ◽  
Vol 77 (6) ◽  
pp. 6607-6628 ◽  
Author(s):  
Xin Yang ◽  
Jiabin Guo ◽  
Tangli Xue ◽  
Kwang-Ting Cheng
2018 ◽  
pp. 777-793
Author(s):  
Srinivasa K. G. ◽  
Satvik Jagannath ◽  
Aakash Nidhi

Mobile devices are changing the way people live. Users have everything on their fingertips and to support them, there are scores of application which add to the usability and comfort. “Know your world better” is an Augmented Reality application developed for Android. This application helps the user to find friends and locate places in close proximity. In this paper we talk about an application that describes a method of augmenting Point of Interests (POI's) on a mobile device. User has to move his phone pointing in a direction of his choice and POI's if any are shown in real time. The user's interest with respect to the environment is inferred from speech or by selecting from the choices; this data is used for information retrieval from the cloud. The result of context-sensitive information retrieval is augmented onto the view of the mobile and provides speech output.


Author(s):  
V. Palma ◽  
R. Spallone ◽  
M. Vitali

<p><strong>Abstract.</strong> This paper presents the most recent developments in a project aimed to the documentation, storage and dissemination of the cultural heritage. The subject of the project are more than 70 Baroque atria in Turin, recognized by critics for their particular unitary vaulted systems Our research team is currently working on digitizing documents and studying ways to enhance and share these results through ICT. In particular, we want to explore possibilities for recognizing and tracing three-dimensional objects in augmented reality (AR) applications connected to the collected data. Recent developments in this field relate to the technology available on widespread mobile devices such as tablets and smartphones, allowing for real-time 3D scanning. Using software prototypes, we want to introduce some problems involved in integrating this technology into digital archives.</p>


2017 ◽  
Vol 92-93 ◽  
pp. 91-103 ◽  
Author(s):  
Wei Fang ◽  
Lianyu Zheng ◽  
Xiangyong Wu

2018 ◽  
Vol 7 (12) ◽  
pp. 479 ◽  
Author(s):  
Piotr Siekański ◽  
Jakub Michoński ◽  
Eryk Bunsch ◽  
Robert Sitnik

Camera pose tracking is a fundamental task in Augmented Reality (AR) applications. In this paper, we present CATCHA, a method to achieve camera pose tracking in cultural heritage interiors with rigorous conservatory policies. Our solution is real-time model-based camera tracking according to textured point cloud, regardless of its registration technique. We achieve this solution using orthographic model rendering that allows us to achieve real-time performance, regardless of point cloud density. Our developed algorithm is used to create a novel tool to help both cultural heritage restorers and individual visitors visually compare the actual state of a culture heritage location with its previously scanned state from the same point of view in real time. The provided application can directly achieve a frame rate of over 15 Hz on VGA frames on a mobile device and over 40 Hz using remote processing. The performance of our approach is evaluated using a model of the King’s Chinese Cabinet (Museum of King Jan III’s Palace at Wilanów, Warsaw, Poland) that was scanned in 2009 using the structured light technique and renovated and scanned again in 2015. Additional tests are performed on a model of the Al Fresco Cabinet in the same museum, scanned using a time-of-flight laser scanner.


2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Hui Wang ◽  
Meng Wang ◽  
Peng Zhao

Sports video is loved by the audience because of its unique charm, so it has high research value and application value to analyze and study the video data of competition. Based on the background of football match, this paper studies the football detection and tracking algorithm in football game video and analyzes the real-time image of real-time mobile devices in sports video augmented reality. Firstly, the image is preprocessed by image graying, image denoising, image binarization, and so on. Secondly, Hough transform is used to locate and detect football, and according to the characteristics of football, Hough transform is improved. Based on the good performance of SIFT algorithm in feature matching, a football tracking algorithm based on SIFT feature matching is proposed, which matches the detected football with the sample football. The simulation results show that the improved Hough transform can effectively detect football and has good antijamming performance. And the designed football tracking algorithm based on SIFT feature matching can accurately track the football trajectory; therefore, the football detection and tracking algorithm designed in this paper is suitable for real-time football monitoring and tracking.


2017 ◽  
Vol 7 (2) ◽  
pp. 120
Author(s):  
Nur Imansyah ◽  
Sri Handani Widiastuti

Getting information in real time at specific times and locations is especially needed when users have high mobility. But often users are not familiar with the area, so difficulty in finding locations and information. The development of technology for location based services and augmented reality makes it easy to get information from available resources in locations using mobile devices equipped with GPS devices. The research aims to combine hotel location based services and augmented reality in android-based mobile device by manipulating virtual objects into real objects through the camera as input and mobile phone display as output.The integration of hotel location based services and augmented reality is useful for hotel users to be able to search hotel information by directing the camera mobile device in the direction of specific targets to be retrieved information. The output of the system is provided in real time on the mobile device display for the user. Output information provided in the direction of location of the hotel object and information about the object of the hotel. 


Sensors ◽  
2017 ◽  
Vol 17 (11) ◽  
pp. 2567 ◽  
Author(s):  
Jin-Chun Piao ◽  
Shin-Dug Kim

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