scholarly journals Histogram Based Hand Recognition System for Augmented Reality

2011 ◽  
Vol 15 (7) ◽  
pp. 1564-1572 ◽  
Author(s):  
Min-Su Ko ◽  
Ji-Sang Yoo
Keyword(s):  
Augmented Reality ◽  
Recognition System ◽  
Hand Recognition

scholarly journals Augmented Reality Maintenance Assistant Using YOLOv5

2021 ◽  
Vol 11 (11) ◽  
pp. 4758
Author(s):  
Ana Malta ◽  
Mateus Mendes ◽  
Torres Farinha
Keyword(s):  
Neural Network ◽  
Deep Learning ◽  
Object Recognition ◽  
Augmented Reality ◽  
Real Time ◽  
Recognition System ◽  
High Accuracy ◽  
Video Streams ◽  
The Neural Network ◽  
Deep Learning Neural Network

Maintenance professionals and other technical staff regularly need to learn to identify new parts in car engines and other equipment. The present work proposes a model of a task assistant based on a deep learning neural network. A YOLOv5 network is used for recognizing some of the constituent parts of an automobile. A dataset of car engine images was created and eight car parts were marked in the images. Then, the neural network was trained to detect each part. The results show that YOLOv5s is able to successfully detect the parts in real time video streams, with high accuracy, thus being useful as an aid to train professionals learning to deal with new equipment using augmented reality. The architecture of an object recognition system using augmented reality glasses is also designed.

scholarly journals INITIAL EVALUATION OF THE POTENTIAL OF SMARTPHONE STEREO-VISION IN MUSEUM VISITS

2019 ◽  
Vol XLII-2/W11 ◽  
pp. 837-842
Author(s):  
A. Masiero ◽  
G. Tucci ◽  
A. Conti ◽  
L. Fiorini ◽  
A. Vettore
Keyword(s):  
Augmented Reality ◽  
Stereo Vision ◽  
3D Model ◽  
New Technologies ◽  
Recognition System ◽  
Neural Network Classifier ◽  
Visual Effects ◽  
Geometric Information ◽  
Traditional Use ◽  
Museum Visit

<p><strong>Abstract.</strong> The recent introduction of new technologies such as augmented reality, machine learning and the worldwide spread of mobile devices provided with imaging, navigation sensors and high computational power can be exploited in order to drammatically change the museum visit experience. Differently from the traditional use of museum docents or audio guides, the introduction of digital technologies already proved to be useful in order to improve the interest of the visitor thanks to the increased interaction and involvement, reached also by means of visual effects and animations. Actually, the availability of 3D representations, augmented reality and navigation abilities directly on the visitor’s device can lead to a personalized visit, enabling the visitor to have an experience tailored on his/her needs. In this framework, this paper aims at investigating the potentialities of smartphone stereo-vision to improve the geometric information about the artworks available on the visitor’s device. More specifically, in this work smartphone stereo-vision will used as a 3D model generation tool in a 3D artwork recognition system based on a neural network classifier.</p>

scholarly journals Moving Object Tracking for SLAM-based Augmented Reality

2021 ◽  
Author(s):  
Douglas Coelho Braga de Oliveira ◽  
Rodrigo Luis de Souza da Silva
Keyword(s):  
Augmented Reality ◽  
Moving Objects ◽  
Recent Literature ◽  
State Of The Art ◽  
Recognition System ◽  
Virtual Object ◽  
Total Occlusion ◽  
Optimization Framework ◽  
Localization And Mapping ◽  
Potential Applications

Augmented Reality (AR) systems based on the Simultaneous Localization and Mapping (SLAM) problem have received much attention in the last few years. SLAM allows AR applications on unprepared environments, i.e., without markers. However, by eliminating the marker object, we lose the referential for virtual object projection and the main source of interaction between real and virtual elements. In the recent literature, we found works that integrate an object recognition system to the SLAM in a way the objects are incorporated into the map. In this work, we propose a novel optimization framework for an object-aware SLAM system capable of simultaneously estimating the camera and moving objects positioning in the map. In this way, we can combine the advantages of both marker- and SLAM-based methods. We implement our proposed framework over state-of-the-art SLAM software and demonstrate potential applications for AR like the total occlusion of the marker object.

Comparison Between 2D and 3D Hand Gesture Interaction for Augmented Reality Applications

2011 ◽  
Author(s):  
Rafael Radkowski ◽  
Christian Stritzke
Keyword(s):  
Augmented Reality ◽  
Gesture Recognition ◽  
Recognition System ◽  
Hand Gesture ◽  
Interaction Techniques ◽  
3D Interaction ◽  
Gesture Interaction ◽  
Depth Images ◽  
2D And 3D ◽  
Hand Gesture Interaction

This paper presents a comparison between 2D and 3D interaction techniques for Augmented Reality (AR) applications. The interaction techniques are based on hand gestures and a computer vision-based hand gesture recognition system. We have compared 2D gestures and 3D gestures for interaction in AR application. The 3D recognition system is based on a video camera, which provides an additional depth image to each 2D color image. Thus, spatial interactions become possible. Our major question during this work was: Do depth images and 3D interaction techniques improve the interaction with AR applications, respectively with virtual 3D objects? Therefore, we have tested and compared the hand gesture recognition systems. The results show two things: First, they show that the depth images facilitate a more robust hand recognition and gesture identification. Second, the results are a strong indication that 3D hand gesture interactions techniques are more intuitive than 2D hand gesture interaction techniques. In summary the results emphasis, that depth images improve the hand gesture interaction for AR applications.

Door Knob Hand Recognition System

2017 ◽  
pp. 259-284
Author(s):  
David Zhang ◽  
Guangming Lu ◽  
Lei Zhang
Keyword(s):  
Recognition System ◽  
Hand Recognition
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