Representational image generation for 3D objects

Official URL: http://dx.doi.org/10.1007/s00371-013-0805-5

Finding good representational images for 3D object exploration is a highly subjective problem in the cognitive field. The “best” or “good” definitions do not depend on any metric. We have explained the VKL distance concept and introduced a novel view descriptor called vSKL distance for finding “good” representational images. The image generation is done by projecting the surfaces of 3D objects onto the screen or any planar surface. The projection process depends on parameters such as camera position, camera vector, up vector, and clipping plane positions. In this work we present a technique to find such camera positions that the 3D object is projected in “good” or “best” way where those subjective definitions are mapped to Information Theoretical distances. We compared greedy view selection integrated vSKL with two well known techniques: VKL and VMI. vSKL performs very close to the other two, hence face coverage perturbation is minimal, but it is 3 to 4 times faster. Furthermore, the saliency information is conveyed to users with generated images.