Rotation-invariant object detection using Complex Matched Filters and second order vector fields

In this paper we introduce two concepts: second order vector fields that describe line-like objects in images and rotation-invariant Complex Matched Filter kernels that can be used to detect object with almost any complexity. We present the theoretical grounds for kernel derivation, object matching using sets of subresponses, object's rotation angle and active area determination. The work of the proposed algorithms is demonstrated on images of an occluded and rotated object.