用活动曲线表示图像

Wenze Hu, Y. Wu, Song-Chun Zhu
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引用次数: 9

摘要

本文提出了一种稀疏图像表示方法,使用自然场景图像中常见的简单几何结构的可变形模板。这些可变形模板包括活动曲线模板和活动角模板。活动曲线模板是由等距放置在恒定曲率的直线段或圆弧段上的Gabor小波元素组成,允许每个Gabor小波元素局部移动其位置和方向,从而使活动曲线模板的原始直线和圆弧段变形以拟合观测图像。活动角模板或角度模板是由两个共享一个共同端点的活动曲线模板组成的,活动曲线模板允许改变其总长度和曲率,从而使原始角模板能够变形以匹配观测图像。然后,本文提出了一种summax地图的分层计算架构,该架构通过从所有这些模板的字典中选择少量的活动曲线和角模板来追求图像的稀疏表示。实验表明,该方法能够找到自然图像的稀疏表示。通过选择和组合活动的曲线和角模板,可以学习对象模板。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Image representation by active curves
This paper proposes a sparse image representation using deformable templates of simple geometric structures that are commonly observed in images of natural scenes. These deformable templates include active curve templates and active corner templates. An active curve template is a composition of Gabor wavelet elements placed with equal spacing on a straight line segment or a circular arc segment of constant curvature, where each Gabor wavelet element is allowed to locally shift its location and orientation, so that the original line and arc segment of the active curve template can be deformed to fit the observed image. An active corner or angle template is a composition of two active curve templates that share a common end point, and the active curve templates are allowed to vary their overall lengths and curvatures, so that the original corner template can deform to match the observed image. This paper then proposes a hierarchical computational architecture of summax maps that pursues a sparse representation of an image by selecting a small number of active curve and corner templates from a dictionary of all such templates. Experiments show that the proposed method is capable of finding sparse representations of natural images. It is also shown that object templates can be learned by selecting and composing active curve and corner templates.
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