The Stereoscopic Zoom

Sergi Pujades, Frédéric Devernay, Laurent Boiron, Rémi Ronfard.

Computation Cameras and Displays, Jul 2017, Honolulu, United States. IEEE, pp.1295-1304, 2017, The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops.

Example image of our Blender Lego dataset.


We study camera models to generate stereoscopic zoom shots, i.e. using very long focal length lenses. Stereoscopic images are usually generated with two cameras. However, we show that two cameras are unable to create compelling stereoscopic images for extreme focal length lenses. Inspired by the practitioners’ use of the long focal length lenses we propose two different configurations: we ” get closer ” to the scene, or we create ” perspective deformations “. Both configurations are build upon state-of-the-art image-based rendering methods allowing the formal deduction of precise parameters of the cameras depending on the scene to be acquired. We present a proof of concept with the acquisition of a representative simplified scene. We discuss the advantages and drawbacks of each configuration.