Get optical flow and object orientation even with lighting changes with INV-Flow2PoseNet
Get optical flow and object orientation even with lighting changes with INV-Flow2PoseNet
INV-Flow2PoseNet: Light-Resistant Rigid Object Pose from Optical Flow of RGB-D Images using Images, Normals and Vertices
arXiv paper abstract https://arxiv.org/abs/2209.06562v1
arXiv PDF paper https://arxiv.org/pdf/2209.06562v1.pdf
… presents a novel architecture for simultaneous estimation of highly accurate optical flows and rigid scene transformations for difficult scenarios where the brightness assumption is violated by strong shading changes.
… standard methods for calculating optical flows or poses are based on the expectation that the appearance of features in the scene remain constant between views.
… presented method fuses texture and geometry information by combining image, vertex and normal data to compute an illumination-invariant optical flow.
By using a coarse-to-fine strategy, globally anchored optical flows are learned, reducing the impact of erroneous shading-based pseudo-correspondences.
Based on the learned optical flows, a second architecture is proposed that predicts robust rigid transformations from the warped vertex and normal maps.
… method has been evaluated on a newly created dataset containing both synthetic and real data with strong rotations and shading effects …
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