I have seen how effective SURF and SIFT can be at feature matching 2d images, but I was wondering if training a cascade filter on a single object would be better for detecting a single object at different orientations and distances.
The goal would be to detect a raised landing pad-like object from a UAV when the object may be at the edge of a wide angle image, at any orientation, and/or from a substantial height. This object will be around a foot cubed and could have distinctive coloring and markings.
Thanks!