Object Recognition in Computational Photography

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Object Recognition in Computational Photography

Computational photography is the convergence of computer vision, computer graphics, the internet and photography.

Computational photography is the convergence of computer vision, computer graphics, the internet and photography.

Rather than relying on optical processes alone, it uses digital capturing and processing techniques to reflect and enhance the visual effects and phenomena of real life in photographic form.

Everyone with a smartphone now has access to computational photography tools. In its iPhones, Apple uses computational photography to achieve a shallow depth of field, while Facebook corrects any 360-degree photos you upload.

Research from Nvidia and the University of California-Santa Barbara has revealed a computational zoom technique, which allows photographers to change the composition of their photographs in real time. Photos are taken in a stack, and then rendered with multiple views.

This would allow photographers to change perspective and the relative size of objects within a photo after it has been taken. Other use cases of computational photography include seamlessly removing or adding objects to scenes, changing shadows, reflections, and other atmospheric touches. Meanwhile, MIT’s CSAIL and Google developed a technique that now automatically retouches and enhances the photos we take with our mobile phones.