The Effect of Pose on the Distribution of Edge Gradients in Omnidirectional Images

Abstract

Images from omnidirectional cameras are used frequently in applications involving artificial intelligence and robotics as a source of rich information about the surroundings. A useful feature that can be extracted from these images is the distribution of gradients of the edges in the scene. This distribution is affected by the pose of the camera on-board a robot at any given location in the environment. This paper investigates the effect of the pose on this distribution. The gradients in the images are extracted and arranged into a histogram which is then compared to the histograms of other images using a chi-squared test. It is found that any differences in the distribution are not specific to either the position or orientation and that there is a significant difference in the distributions of two separate locations. This can aid in the localisation of robots when navigating.