Enhanced key-point detection for plenoptic imaging

Abstract

Standard imaging techniques do not get as much information from a scene as light-field imaging. Light-field (LF) cameras can measure the light intensity reflected by an object and, most importantly, the direction of its light rays. This information can be used in different applications, such as depth estimation, in-plane focusing, creating full-focused images, etc. However, standard key-point detectors often employed in computer vision applications cannot be applied directly to plenoptic images due to the nature of raw LF images. This work presents an approach for key-point detection dedicated to plenoptic images. Our method allows using of conventional key-point detector methods. It forces the detection of this key-point in a set of micro-images of the raw LF image. Obtaining this important number of key-points is essential for applications that require finding additional correspondences in the raw space, such as disparity estimation, indirect visual odometry techniques, and others. The approach is set to the test by modifying the Harris key-point detector.