Applied Vision
Authors: Ido Akov (Austrian Institute of Technology) , Roman Pflugfelder (Austrian Institute of Technology) , Daniel Cremers (Technical University of Munich)
Fragmented occlusion, as encountered in through-foliage observation, makes monocular motion estimation difficult because the target is visible only through sparse, discontinuous image fragments. We estimate motion by warping frames under a parametric model and maximizing the contrast of their integrated image. Although effective for 2DoF translation, this objective becomes ill-conditioned for 4DoF similarity motion. To analyze this, we derive a Fourier-domain reformulation that exposes the optimization structure and shows that static occlusion biases the objective toward zero motion. This motivates a decoupled 4DoF pipeline in which rotation and scale are estimated separately from translation. On synthetic videos with controlled fragmented occlusion, the Fourier formulation matches the spatial baseline at low-to-mid occlusion while converging faster, and the decoupled pipeline restores reliable translation recovery where joint 4DoF optimization fails.
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How to Cite: Akov, I. , Pflugfelder, R. & Cremers, D. (2026) “Fourier contrast optimization for occluded motion estimation”, Proceedings of the Austrian Symposium on AI, Robotics, and Vision. 3(1).