Communications of the ACM
Natural World Empowers Future of Computer Vision
The images generated by the system and automatically labeled can then be used to train a robot to recognize and locate objects using only an image as input.
Credit: Jia Deng et al
An open source software system developed by Princeton University researchers aims to improve the training of computer vision systems by quickly generating an unlimited number of photorealistic scenes of the natural world.
The Infinigen system uses randomized mathematical rules to produce natural-looking three-dimensional (3D) objects and synthetic representations of natural phenomena.
Each image is generated programmatically, which involves developing a virtual world and populating it with digital objects, which allows for automatic labeling and training computer vision systems to identify and locate objects with only an image as input.
Princeton's Jia Deng said the researchers expect Infinigen will prove “a useful resource not just for creating training data for computer vision, but also for augmented and virtual reality, game development, film-making, 3D printing, and content generation in general."
From Princeton University
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