Fast object recognition using dynamic programming from combination of salient line groups
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摘要
This paper presents a new method of grouping and matching line segments to recognize objects. We propose a dynamic programming-based formulation extracting salient line patterns by defining a robust and stable geometric representation that is based on perceptual organizations. As the endpoint proximity, we detect several junctions from image lines. We then search for junction groups by using the collinear constraint between the junctions. Junction groups similar to the model are searched in the scene, based on a local comparison. A DP-based search algorithm reduces the time complexity for the search of the model lines in the scene. The system is able to find reasonable line groups in a short time.
论文关键词:Feature matching,Dynamic programming,Perceptual grouping,Object recognition
论文评审过程:Received 21 August 2001, Accepted 28 January 2002, Available online 17 February 2006.
论文官网地址:https://doi.org/10.1016/S0031-3203(02)00046-8