Incorporation of Panoramic View in Fall Detection Using Omnidirectional Camera

Abstract

Falling is one of the major problems that threaten the health of the elderly and particularly dangerous for people that live alone. Recently, surveillance systems using omnidirectional cameras in general and fisheye cameras particularly have become an attractive choice, as they provide a wide Field of Vision without the need for multiple cameras. However, objects captured by fisheye cameras are highly distorted, therefore computer vision approaches that are developed for conventional cameras require modification to work with such systems . The aim of this work is to incorporate the de-warping of fisheye image using polar to Cartesian transformation to generate a panoramic view. Objects are detected by background subtraction method. Depending on the objects lay inside or outside of a center circle of the omnidirectional frame, features based on contour and rotated bounding box of the objects, are extracted correspondingly on original omnidirectional view or panoramic view. Experiments show that by incorporating both panoramic and omnidirectional view, we can achieve significant improvement in fall detection, particularly in peripheral areas. This result could be a useful reference for further studies.