1. Development of VR Glasses
<Your Names>
Supervisor <Title and Name of Your Supervisor>
Example Poster
A2 (42x59.4 cm)
Faculty of Engineering and Applied Sciences,
Department of Computer Engineering, Bahçeşehir University.
A headset with glasses that conveys depth perception to the user and tracks his head movement is designed. It replicates a real environment or creates an imaginary setting. The headset is marked with distinctive markers and tracked by a camera. After the detection of markers, 3D pose estimation of camera to the headset is performed to gain the position in the space and the orientation of the headset.
Abstract
Main Components of the Tracking System and their dependencies 1
Main Components
Frustum, Commercial vR Headset for smart devices, Smart Device, PC with camera.
Design and Implementation
A Frustum-shaped model is mounted on the headset with Aruco markers sticked to it. The camera detects the pattern of each marker and gets its coordinate in 2D image and matches them with the 3D coordinates of the same points to solve the perspective-n-points problem(pose estimation). This will allow us to track the headset position and orientation.
The VR headset prototype is successfully tracked by the output of tracking system, rotation and translation vector. Further improvements to the hardware and software would allow for more robust tracking to the headset. Besides everyone would have chance to get the full immersive VR experience.
Conclusion
References:
[1] S. Garrido-Jurado,et all
Computing and Numerical Analysis Department, Córdoba University, Edificio Einstein, 3a planta, Campus de Rabanales, Córdoba, Spain. Automatic generation and detection of highly reliable fiducial markers under occlusion (June, 2014) Computer and Machine Vision:Theory, Algorithms,Practicalities
Fourth Edition E. R. DAVIES Department of Physics Royal Holloway, University of London, Egham, Surrey, UK
[3] Mastering OpenCV with Practical Computer Vision Projects. Daniel.Baggio et al, page 72
[4]
[5] Zhang, Z. "A Flexible New Technique for Camera Calibration." IEEE Transactions on Pattern Analysis and Machine Intelligence. Vol. 22, No. 11, 2000, pp. 1330–1334.