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Plenoptical cameras

Novel concepts for three-dimensional vision

plenoptikprinzip

Like most mammals’, the three-dimensional vision of humans is dependent on stereoscopic vision, which is to say the separate vision of left and right eye. The information of three-dimensional depth, gained by the disparity of the two different images, is produced in the brain. This is part and parcel of the failure of the Cyclops in Homer’s Ulysses. Since he lacked the information of 3D depth, he could not locate his opponent.


Technically speaking, it is quite challenging to miniaturize systems that are based on binocular vision. Conventional 3D devices consist of two ‚eyes’, i.e. little cameras made of lens and image sensor. Novel plenoptical cameras (from Latin: plenum = full) can image objects with only one camera system, a so-called monocular.

With a customized lens array that is put in the image plane of the main lens (see figure below), it is possible to determine the direction of the light beam in addition to the x/y coordinates. Taken together, this information is the basis of the ensuing calculation of the depth of field. Thus, the plenoptical camera imitates the binocular vision of the human eye. The Cyclops could have located Ulysses easily and won the fight.

plenoptische kameras
Current plenoptical cameras are still limited with regard to depth of field and spatial resolution. This is the challenge we tackle with our active micro-optical components. Our piezoelectric actuators and fluidic micro-iris arrays will make the plenoptical cameras not only smaller, faster and more accurate, but just as tunable as the biological role model.


In addition, we combine plenoptical cameras with customized microscopes in order to obtain three-dimensional images of biological probes. Here, an active polarization component is inserted in the optical beam path, which helps to make even those probes visible, that are generally weak in contrast even under changing conditions.
Apart from such medical application, plenoptical cameras can also enhance machine vision for process monitoring.

  

 

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