Abstract

Detecting objects in three-dimensional (3D) space may be useful for various applications. We present a method to detect the 3D locations of objects using computationally reconstructed images obtained by integral imaging. The new algorithm exploits the space-variant blurring properties of the reconstructed images to detect and isolate objects at their depth locations, while removing traces of objects from other depths. With regard to previous work, the proposed method is more efficient and more resistant to noise; it gives more information about the detected object’s depth, and improves object isolation and presentation.

© 2015 Optical Society of America

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