Axial-Cones: Modeling Spherical Catadioptric Cameras
for Wide-Angle Light Field Rendering

Yuichi Taguchi, Amit Agrawal, Ashok Veeraraghavan, Srikumar Ramalingam and Ramesh Raskar

Mitsubishi Electric Research Labs (MERL)    &    MIT Media Lab

SIGGRAPH Asia 2010

Photo captured by a camera looking at 12 Spherical Mirrors. The scene consist of a person trying to catch a ball outdoors.

Modeling of Spherical Mirrors using Virtual Axial-Cone Cameras

Output Wide-Angle Refocusing Results and Depth Maps

Photo captured by a camera looking at 12 Refractive Acrylic Ball Lenses

Modeling of Refractive Spheres using Virtual Axial-Cone Cameras

Output Wide-Angle Refocusing Results and Depth Maps


Single shot wide-angle light field capture and rendering system using an array of spherical mirrors and an array of refractive spheres. Our axial-cone modeling allows GPU based rendering for wide-angle digital refocusing and dense volumetric 3D reconstruction.


Catadioptric imaging systems are commonly used for wide-angle imaging, but lead to multi-perspective images which do not allow algorithms designed for perspective cameras to be used. Efficient use of such systems requires accurate geometric ray modeling as well as fast algorithms. We present accurate geometric modeling of the multi-perspective photo captured with a spherical catadioptric imaging system using axial-cone cameras: multiple perspective cameras lying on an axis each with a different viewpoint and a different cone of rays. This modeling avoids geometric approximations and allows several algorithms developed for perspective cameras to be applied to multi-perspective catadioptric cameras.

We demonstrate axial-cone modeling in the context of rendering wide-angle light fields, captured using a spherical mirror array. We present several applications such as spherical distortion correction, digital refocusing for artistic depth of field effects in wide-angle scenes, and wide-angle dense depth estimation. Our GPU implementation using axial-cone modeling achieves up to three orders of magnitude speed up over ray tracing for these applications.

Paper  (Low res pdf 10 MB)

Talk Slides

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