
handle: 10281/350452 , 11562/1000143 , 11573/1360134 , 11585/737542
We introduce GFrames, a novel local reference frame (LRF) construction for 3D meshes and point clouds. GFrames are based on the computation of the intrinsic gradient of a scalar field defined on top of the input shape. The resulting tangent vector field defines a repeatable tangent direction of the local frame at each point; importantly, it directly inherits the properties and invariance classes of the underlying scalar function, making it remarkably robust under strong sampling artifacts, vertex noise, as well as non-rigid deformations. Existing local descriptors can directly benefit from our repeatable frames, as we showcase in a selection of 3D vision and shape analysis applications where we demonstrate state-of-the-art performance in a variety of challenging settings.
3D from Multiview and Sensors; Categorization; Low-level Vision; Motion and Tracking; Recognition: Detection; Retrieval, 3D from Multiview and Sensors; Categorization; Low-level Vision; Motion and Tracking; Recognition: Detection; Retrieval;, shape analysis, shape matching, local reference frame, shape descriptor. gradient, local reference frame; 3D meshes; shape analysis
3D from Multiview and Sensors; Categorization; Low-level Vision; Motion and Tracking; Recognition: Detection; Retrieval, 3D from Multiview and Sensors; Categorization; Low-level Vision; Motion and Tracking; Recognition: Detection; Retrieval;, shape analysis, shape matching, local reference frame, shape descriptor. gradient, local reference frame; 3D meshes; shape analysis
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