  Pedestrian detection in images is a topic that has been studied extensively,
but existing detectors designed for perspective images do not perform as
successfully on images taken with top-view fisheye cameras, mainly due to the
orientation variation of people in such images. In our proposed approach,
several perspective views are generated from a fisheye image and then
concatenated to form a composite image. As pedestrians in this composite image
are more likely to be upright, existing detectors designed and trained for
perspective images can be applied directly without additional training. We also
describe a new method of mapping detection bounding boxes from the perspective
views to the fisheye frame. The detection performance on several public
datasets compare favorably with state-of-the-art results.
