Virtual Block Augmented Reality Game Using Freehand Gesture Interaction

Augmented Reality (AR) manages to bring a virtual environment into a real-world environment seamlessly. As AR has been recognised as advancing technology, AR brings future changes to the learning process. The goal of this study is to use freehand gestures to create a virtual block game in AR. First of all, the stages of this study are to explore block games and freehand movements by using Leap Motion. Secondly, the design and development of Leap Motion virtual block games, and thirdly, the implementation of free-hand gesture interaction virtual block games. The paper explains about virtual blocks AR game using freehand gesture. AR tracking system with real hand gesture recognition system is merged to execute the freehand gesture. A prototype virtual block has been described in this paper. The paper ends with the conclusion and future works.

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

Volume 2: 31st Computers and Information in Engineering Conference, Parts A and B ◽

10.1115/detc2011-48155 ◽

2011 ◽

Cited By ~ 2

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.

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CUDA-based real-time hand gesture interaction and visualization for CT volume dataset using leap motion

The Visual Computer ◽

10.1007/s00371-016-1209-0 ◽

2016 ◽

Vol 32 (3) ◽

pp. 359-370 ◽

Cited By ~ 11

Author(s):

Junchen Shen ◽

Yanlin Luo ◽

Zhongke Wu ◽

Yun Tian ◽

Qingqiong Deng

Keyword(s):

Real Time ◽

Hand Gesture ◽

Leap Motion ◽

Gesture Interaction ◽

Hand Gesture Interaction ◽

Ct Volume

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Computer-Assisted Culture Learning in an Online Augmented Reality Environment Based on Free-Hand Gesture Interaction

IEEE Transactions on Learning Technologies ◽

10.1109/tlt.2014.2307297 ◽

2014 ◽

Vol 7 (2) ◽

pp. 107-117 ◽

Cited By ~ 23

Author(s):

Mau-Tsuen Yang ◽

Wan-Che Liao

Keyword(s):

Augmented Reality ◽

Hand Gesture ◽

Computer Assisted ◽

Culture Learning ◽

Gesture Interaction ◽

Hand Gesture Interaction

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GPU-Based Realtime Hand Gesture Interaction and Rendering for Volume Datasets Using Leap Motion

10.1109/cw.2014.20 ◽

2014 ◽

Cited By ~ 5

Author(s):

Junchen Shen ◽

Yanlin Luo ◽

Xingce Wang ◽

Zhongke Wu ◽

Mingquan Zhou

Keyword(s):

Hand Gesture ◽

Leap Motion ◽

Gesture Interaction ◽

Hand Gesture Interaction

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Hand Gesture Interaction with a Low-Resolution Infrared Image Sensor on an Inner Wrist

Proceedings of the International Conference on Advanced Visual Interfaces ◽

10.1145/3399715.3399858 ◽

2020 ◽

Author(s):

Yuki Yamato ◽

Yutaro Suzuki ◽

Kodai Sekimori ◽

Buntarou Shizuki ◽

Shin Takahashi

Keyword(s):

Infrared Image ◽

Image Sensor ◽

Hand Gesture ◽

Low Resolution ◽

Gesture Interaction ◽

Hand Gesture Interaction

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An Adaptive Superpixel Based Hand Gesture Tracking and Recognition System

The Scientific World JOURNAL ◽

10.1155/2014/849069 ◽

2014 ◽

Vol 2014 ◽

pp. 1-12 ◽

Cited By ~ 5

Author(s):

Hong-Min Zhu ◽

Chi-Man Pun

Keyword(s):

Template Matching ◽

Tracking System ◽

Recognition System ◽

Appearance Model ◽

Hand Gesture ◽

Svm Classifier ◽

Motion Trajectory ◽

Hand Motion ◽

Target Hand ◽

Gesture Tracking

We propose an adaptive and robust superpixel based hand gesture tracking system, in which hand gestures drawn in free air are recognized from their motion trajectories. First we employed the motion detection of superpixels and unsupervised image segmentation to detect the moving target hand using the first few frames of the input video sequence. Then the hand appearance model is constructed from its surrounding superpixels. By incorporating the failure recovery and template matching in the tracking process, the target hand is tracked by an adaptive superpixel based tracking algorithm, where the problem of hand deformation, view-dependent appearance invariance, fast motion, and background confusion can be well handled to extract the correct hand motion trajectory. Finally, the hand gesture is recognized by the extracted motion trajectory with a trained SVM classifier. Experimental results show that our proposed system can achieve better performance compared to the existing state-of-the-art methods with the recognition accuracy 99.17% for easy set and 98.57 for hard set.

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