Real-Time Hand Palm Detection and Tracking Augmented Reality Game Using Lucas Kanade Optical Flow Combined with Color Blob Detection

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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Real-Time Detection and Tracking for Augmented Reality on Mobile Phones

IEEE Transactions on Visualization and Computer Graphics ◽

10.1109/tvcg.2009.99 ◽

2010 ◽

Vol 16 (3) ◽

pp. 355-368 ◽

Cited By ~ 197

Author(s):

D. Wagner ◽

G. Reitmayr ◽

A. Mulloni ◽

T. Drummond ◽

D. Schmalstieg

Keyword(s):

Augmented Reality ◽

Real Time ◽

Mobile Phones ◽

Detection And Tracking ◽

Real Time Detection

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Dynamic Targets Detection for Robotic Applications Using Panoramic Camera Based on Optical Flow

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.376.455 ◽

2013 ◽

Vol 376 ◽

pp. 455-460

Author(s):

Wei Zhu ◽

Li Tian ◽

Fang Di ◽

Jian Li Li ◽

Ke Jie Li

Keyword(s):

Optical Flow ◽

Real Time ◽

High Speed ◽

Moving Objects ◽

Inspection System ◽

Flow Method ◽

Optical Flow Method ◽

Detection And Tracking ◽

Optical Flows ◽

Sequential Images

Optical flow method is an important and valid method in the field of detection and tracking of moving objects for robot inspection system. Due to the traditional Horn-Schunck optical flow method and Lucas-Kanade optical flow method cannot meet the demands of real-time and accuracy simultaneously, an improved optical flow method based on Gaussian image pyramid is proposed. The layered structure of the images can be obtained by desampling of the original sequential images so that the motion with the high speed can be changed into continuous motion with lower speed. Then the optical flows of corner points of the lowest layer will be calculated by the LK method and be delivered to the upper layer and so on. Thus the estimated optical flow vectors of the original sequential images will be obtained. In this way, the requirement of accuracy and real time could be met for robotic moving obstacle recognition.

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Sports Video Augmented Reality Real-Time Image Analysis of Mobile Devices

Mathematical Problems in Engineering ◽

10.1155/2021/9963524 ◽

2021 ◽

Vol 2021 ◽

pp. 1-13

Author(s):

Hui Wang ◽

Meng Wang ◽

Peng Zhao

Keyword(s):

Augmented Reality ◽

Real Time ◽

Mobile Devices ◽

Hough Transform ◽

Feature Matching ◽

Tracking Algorithm ◽

Sports Video ◽

Detection And Tracking ◽

Real Time Image ◽

Time Image

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.

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Evacuation training using scenario-based augmented reality game

the 5th International Conference on Virtual and Augmented Reality in Education ◽

10.46354/i3m.2019.vare.007 ◽

2019 ◽

Author(s):

Hiroyuki Mitsuhara ◽

Masami Shishibori

Keyword(s):

Augmented Reality ◽

Computer Graphics ◽

Real Time ◽

Real World ◽

Time Limit ◽

The Real ◽

Head Mounted Display ◽

Digital Contents ◽

Disaster Education ◽

Augmented Reality Game

"Evacuation training is important as disaster education that covers how to survive disasters. However, traditional evacuation training does not provide realistic simulated evacuation experience (SEE). To provide the such, we developed game-based evacuation training (GBET), where trainees are required to reach a shelter in the real world within a time limit while making decisions against virtual disaster situations presented as digital contents (e.g. video and single-choice question) on GPS-enabled smartphones or tablets. However, the GBET was insufficient in the audiovisual reality. To provide a more realistic SEE, we created an evacuation training using scenario-based augmented reality (AR) game that integrates marker-based AR and scenariobased game. Although only applicable in indoor activities, the evacuation training (the extended GBET system) presents AR that expresses disaster situations (e.g. flood and fire) by superimposing threedimensional computer graphics onto the real-time view through a handheld head-mounted display."

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