α-shapes for local feature detection
نویسندگان
چکیده
منابع مشابه
WαSH: Weighted α-Shapes for Local Feature Detection
Depending on the application, local feature detectors should comply with properties that are often contradictory, e.g . distinctiveness vs. robustness. Providing a good balance is a standing problem in the field. In this direction, we propose a novel approach for local feature detection starting from sampled edges. The detector is based on shape stability measures across the weighted α-filtrati...
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Local feature detection has been an essential part of many methods for computer vision applications like large scale image retrieval, object detection, or tracking. Recently, structure-guided feature detectors have been proposed, exploiting image edges to accurately capture local shape. Among them, the WαSH detector [Varytimidis et al., 2012] starts from sampling binary edges and exploits α-sha...
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Some recent works have addressed the object recognition problem by representing objects as the composition of independent image parts, where each part is modeled with “low-level” features. One of the problems to address is the choice of the low-level features to appropriately describe the individual image parts. Several feature types have been proposed, like edges, corners, ridges, Gaussian der...
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Form feature modeling is a much used shape modeling technique that offers high-level control over a shape. When a feature-based interpretation of shape data is not available, e.g. when a shape is obtained by a laser range scanner or from a database of shapes, then the features must be reconstructed through feature recognition. Many methods for the recognition of machining features exist, but th...
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ژورنال
عنوان ژورنال: Pattern Recognition
سال: 2016
ISSN: 0031-3203
DOI: 10.1016/j.patcog.2015.08.016