Real-time 3D cube detection and tracking using depth sensor for interactive augmented reality system

Author(s):  
Kwang Hee Won ◽  
Soon Ki Jung
2019 ◽  
Vol 9 (19) ◽  
pp. 4019 ◽  
Author(s):  
Sung ◽  
Ma ◽  
Choi ◽  
Hong

Physics education applications using augmented reality technology, which has been developed extensively in recent years, have a lot of restrictions in terms of performance and accuracy. The purpose of our research is to develop a real-time simulation system for physics education that is based on parallel processing. In this paper, we present a video see-through AR (Augmented Reality) system that includes an environment recognizer using a depth image of Microsoft’s Kinect V2 and a real-time soft body simulator based on parallel processing using GPU (Graphic Processing Unit). Soft body simulation can provide more realistic simulation results than rigid body simulation, so it can be more effective in systems for physics education. We have designed and implemented a system that provides the physical deformation and movement of 3D volumetric objects, and uses them in education. To verify the usefulness of the proposed system, we conducted a questionnaire survey of 10 students majoring in physics education. As a result of the questionnaire survey, 93% of respondents answered that they would like to use it for education. We plan to use the stand-alone AR device including one or more cameras to improve the system in the future.


Symmetry ◽  
2015 ◽  
Vol 7 (1) ◽  
pp. 182-192 ◽  
Author(s):  
Jaewoon Lee ◽  
Yeonjin Kim ◽  
Myeong-Hyeon Heo ◽  
Dongho Kim ◽  
Byeong-Seok Shin

2016 ◽  
Author(s):  
Donny Tytgat ◽  
Maarten Aerts ◽  
Jeroen De Busser ◽  
Sammy Lievens ◽  
Patrice Rondao Alface ◽  
...  

Author(s):  
Ankur Kumar

Augmented Reality (AR), which blends virtual information with the real environment in real-time performance, is constantly evolving and becoming more sophisticated and robust. It is critical to ensure that the augmented reality system is accepted and successful. This paper primarily discusses the current state of AR applications and the various fields in which AR is being used.


2021 ◽  
pp. 1-1
Author(s):  
Pasquale Arpaia ◽  
Egidio De Benedetto ◽  
Concetta Anna Dodaro ◽  
Luigi Duraccio ◽  
Giuseppe Servillo

2020 ◽  
Vol 6 (1) ◽  
Author(s):  
Christian Kunz ◽  
Paulina Maurer ◽  
Fabian Kees ◽  
Pit Henrich ◽  
Christian Marzi ◽  
...  

AbstractPatient tracking is an essential part in a surgical augmented reality system for correct hologram to patient registration. Augmented reality can support a surgeon with visual assistance to navigate more precisely during neurosurgical interventions. In this work, a system for patient tracking based on infrared markers is proposed. These markers are widely used in medical applications and meet the special medical requirements such as sterilizability. A tracking accuracy of 0.76 mm is achieved when using the near field reflectivity and depth sensor of the HoloLens. On the HoloLens a performance of 55–60 fps is reached, which grants a sufficiently stable placement of the holograms in the operating room.


The Fingertip Detection acts a specific role in most of the vision based applications. The latest technologies like virtual reality and augmented reality actually follows this fingertip detection concept as its foundation. It is also helpful for Human Computer Interaction (HCI). So fingertip detection and tracking can be applied from games to robot control, from augmented reality to smart homes. The most important interesting field of fingertip detection is the gesture recognition related applications. In the context of interaction with the machines, gestures are the most simplest and efficient means of communication. This paper analyses the various works done in the areas of fingertip detection. A review on various real time fingertip methods is explained with different techniques and tools. Some challenges and research directions are also highlighted. Many researchers uses fingertip detection in HCI systems those have many applications in user identification, smart home etc. A comparison of results by different researchers is also included.


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