Inverse perspective mapping simplifies optical flow computation and obstacle detection

By H. Mallot, Heinrich H. Bülthoff, James J. Little, S. Bohrer. Biological cybernetics, 2004

349 citations recorded by the source corpus.

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On-road vehicle detection: a review (2006, methodology): “Instead of warping the right image onto the left image, Bertozzi and Broggi [16], [56] computed the IPM of both the right and left images.”
A new performance measure and evaluation benchmark for road detection algorithms (2013, background): “The metric road space can be represented in the so-called Bird’s Eye View (BEV) [17] by assuming a flat world for the transformation from the perspective image to the BEV space.”
A survey of video processing techniques for traffic applications (2003, methodology): “[94] deﬁnes patches of similar spatial characteristics in each frame and uses local voting over the output of a correlation-type motion detector to detect moving objects.”
VectorMapNet: End-to-end Vectorized HD Map Learning (2022, methodology): “VectorMapNet does not rely on certain feature transformation approaches and we opt to use a simple but popular variant of IPM, which produces BEV features of F I BEV ∈ R W × H × C 1 .”
MapTR: Structured Modeling and Learning for Online Vectorized HD Map Construction (2022, methodology): “MapTR is compatible with other transformation methods and maintains stable performance, e.g. , CVT (Zhou & Kr¨ahenb¨uhl, 2022), LSS (Philion & Fidler, 2020; Liu et al., 2022c; Li et al., 2022b; Huang et al., 2021), Deformable Attention (Li et al., 2022c; Zhu et al., 2021) and IPM (Mallot et al., 199”