Volograms Releases the Volu App for Easy AR and VR Content Creation
Volu App

Volograms Releases the Volu App for Easy AR and VR Content Creation

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Artificial intelligence and volumetric video firm Volograms has released the public version of its 3D content creation app, Volu. The application uses deep learning and computer vision technologies to facilitate AI-powered mobile content creation for its users. The app enables the users to easily create, share and play with immersive, dynamic augmented reality and virtual reality content.

“Augmented and virtual reality will change our communication patterns and our everyday lives, similar to the advent of the internet, social media, and smartphones,” stated Volograms CEO and Co-founder, Rafael Pagés.

“Eventually, it will be ubiquitous. However, just like every other technology leap, first, it needs to become more accessible. Putting the power of dynamic 3D content creation into every hand, pocket, or purse carrying a smartphone with our Volu app is the first step. We are enabling user-generated content for AR by turning standard smartphone cameras into AR-ready cameras.”

Before the final release, the company fine-tuned key capabilities within the new version of the app based on feedback from thousands of Volu beta users around the globe. They worked on enhancing reliability, speeding 3D reconstruction, incorporating a self-capture timer, and adding new creative effects and algorithms to improve the quality of the app’s output.

The key app features comprise single-view volumetric capture, which enables 3D reconstruction from a single mobile camera. Automatic foreground segmentation eliminates the need for a green screen and allows app usage in uncontrolled environments, such as the outdoors. Markerless estimation enables 3D-skeleton estimation to precisely capture human movements without any additional sensors.

The app is also compatible with advanced sensors, such as LiDAR, to allow depth-based perspective correction and generate more accurate results. It enables comprehensive cloud computing processing, keyframe-based sequence encoding and compression, and integration with machine learning tools. Furthermore, it would eventually allow the shift towards real-time streaming with 5G.

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