An artificial compound eye system is the bionic system of natural compound eyes with much wider field-of-view, better capacity to detect moving objects and higher sensitivity to light intensity than ordinary single-aperture eyes. In recent years, renewed attention has been paid to the artificial compound eyes, due to their better characteristics inheriting from insect compound eyes than ordinary optical imaging systems. This paper provides a comprehensive survey of the state-of-the-art work on artificial compound eyes. This review starts from natural compound eyes to artificial compound eyes including their system design, theoretical development and applications. The survey of artificial compound eyes is developed in terms of two main types: planar and curved artificial compound eyes. Finally, the most promising future research developments are highlighted.

In recent years, much attention has been paid to the electronic cluster eye (eCley), a new type of artificial compound eyes, because of its small size, wide field of view (FOV) and sensitivity to motion objects. An eCley is composed of a certain number of optical channels organized as an array. Each optical channel spans a small and fixed field of view (FOV). To obtain a complete image with a full FOV, the images from all the optical channels are required to be fused together. The parallax from unparallel neighboring optical channels in eCley may lead to reconstructed image blurring and incorrectly estimated depth. To solve this problem, this paper proposes a geometry based three-dimensional image processing method (G3D) for eCley to obtain a complete focused image and dense depth map. In G3D, we derive the geometry relationship of optical channels in eCley to obtain the mathematical relation between the parallax and depth among unparallel neighboring optical channels. Based on the geometry relationship, all of the optical channels are used to estimate the depth map and reconstruct a focused image. Subsequently, by using an edge-aware interpolation method, we can further gain a sharply focused image and a depth map. The effectiveness of the proposed method is verified by the experimental results.

An artificial compound eye (ACE) is a bio-inspired vision sensor which mimics a natural compound eye (typical of insects). This artificial eye is able to visualize large fields of the outside world through multi-aperture. Due to its functioning, the ACE is subject to optical flow, that is an apparent motion of the object visualized by the eye. This paper proposes a method to estimate the optical flow based on capturing multiple images (multi-aperture).In this method, based on descriptors-based initial optical flows, a unified global energy function is presented to incorporate the information of multi-aperture and simultaneously recover the optical flows of multi-aperture. The energy function imposes a compound flow fields consistency assumption along with the brightness constancy and piecewise smoothness assumptions. This formula efficiently binds the flow field in time and space, and further enables view-consistent optical flow estimation. Experimental results on real and synthetic data demonstrate that the proposed method recovers view-consistent optical flows crossed multi-aperture and performs better than other optical flow methods on the multi-aperture images.