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• W2468932261 abstract "This paper presents an algorithm coined BORDER (Bounding Oriented-Rectangle Descriptors for Enclosed Regions) for texture-less object recognition. By fusing a regional object encompassment concept with descriptor-based pipelines, we extend local-patches into scalable object-sized oriented rectangles for optimal object information encapsulation with minimal outliers. We correspondingly introduce a modified line-segment detection technique termed Linelets to stabilize keypoint repeatability in homogenous conditions. In addition, a unique sampling technique facilitates the incorporation of robust angle primitives to produce discriminative rotation-invariant descriptors. BORDER's high competence in object recognition particularly excels in homogenous conditions obtaining superior detection rates in the presence of high-clutter, occlusion and scale-rotation changes when compared with modern state-of-the-art texture-less object detectors such as BOLD and LINE2D on public texture-less object databases." @default.
• W2468932261 created "2016-07-22" @default.
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• W2468932261 date "2016-06-01" @default.
• W2468932261 modified "2023-10-17" @default.
• W2468932261 title "BORDER: An Oriented Rectangles Approach to Texture-Less Object Recognition" @default.
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• W2468932261 doi "https://doi.org/10.1109/cvpr.2016.312" @default.
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