  In this paper, we introduce a moving object detection algorithm for fisheye
cameras used in autonomous driving. We reformulate the three commonly used
constraints in rectilinear images (epipolar, positive depth and positive height
constraints) to spherical coordinates which is invariant to specific camera
configuration once the calibration is known. One of the main challenging use
case in autonomous driving is to detect parallel moving objects which suffer
from motion-parallax ambiguity. To alleviate this, we formulate an additional
fourth constraint, called the anti-parallel constraint, which aids the
detection of objects with motion that mirrors the ego-vehicle possible. We
analyze the proposed algorithm in different scenarios and demonstrate that it
works effectively operating directly on fisheye images.
