Stereopsis is the computation of depth information from views
acquired simultaneously from different points in space. For many
years, stereopsis was thought to be confined to primates and other
mammals with front-facing eyes. However, stereopsis has now been
demonstrated in many other animals, including lateral-eyed prey
mammals, birds, amphibians and invertebrates. The diversity of
animals known to have stereo vision allows us to begin to investigate
ideas about its evolution and the underlying selective pressures in
different animals. It also further prompts the question of whether all
animals have evolved essentially the same algorithms to implement
stereopsis. If so, this must be the best way to do stereo vision, and
should be implemented by engineers in machine stereopsis.
Conversely, if animals have evolved a range of stereo algorithms in
response to different pressures, that could inspire novel forms of
machine stereopsis appropriate for distinct environments, tasks or
constraints. As a first step towards addressing these ideas, we here
review our current knowledge of stereo vision in animals, with a view
towards outlining common principles about the evolution, function
and mechanisms of stereo vision across the animal kingdom. We
conclude by outlining avenues for future work, including research into
possible new mechanisms of stereo vision, with implications for
machine vision and the role of stereopsis in the evolution of
camouflage.
acquired simultaneously from different points in space. For many
years, stereopsis was thought to be confined to primates and other
mammals with front-facing eyes. However, stereopsis has now been
demonstrated in many other animals, including lateral-eyed prey
mammals, birds, amphibians and invertebrates. The diversity of
animals known to have stereo vision allows us to begin to investigate
ideas about its evolution and the underlying selective pressures in
different animals. It also further prompts the question of whether all
animals have evolved essentially the same algorithms to implement
stereopsis. If so, this must be the best way to do stereo vision, and
should be implemented by engineers in machine stereopsis.
Conversely, if animals have evolved a range of stereo algorithms in
response to different pressures, that could inspire novel forms of
machine stereopsis appropriate for distinct environments, tasks or
constraints. As a first step towards addressing these ideas, we here
review our current knowledge of stereo vision in animals, with a view
towards outlining common principles about the evolution, function
and mechanisms of stereo vision across the animal kingdom. We
conclude by outlining avenues for future work, including research into
possible new mechanisms of stereo vision, with implications for
machine vision and the role of stereopsis in the evolution of
camouflage.