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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