Reflectance based object recognition
Reflectance based object recognition
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DOI：
10.1007/bf00128232
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发表时间：
1996-03
影响因子：
19.5
通讯作者：
S. Nayar;R. Bolle
中科院分区：
文献类型：
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作者：
S. Nayar;R. Bolle
光滑曲面上相邻的点具有相似的表面法线和光照条件。因此，它们的亮度值可以用来计算它们的反射率系数的比值。基于这种观察，我们开发了一种算法，该算法可以估计图像中每个区域相对于其背景的反射率。该算法是高效的，因为它计算比例的所有图像区域在仅仅两个光栅扫描。区域反射率代表了一种不受光照和成像参数影响的物理性质。通过实验验证了比率不变量的准确性和鲁棒性。比率不变量用于从场景的单一亮度图像中识别目标。对象模型自动获取，并使用散列表表示。提出了利用场景区域的比例估计及其几何属性来索引哈希表的识别和姿态估计算法。结果是对图像中物体存在的假设。使用场景中其他区域的比例和位置验证了这一假设。这种识别方法对带有文字和图片的物体是有效的。对光照变化、遮挡和阴影的图像进行了识别实验。本文最后讨论了反射率和几何在视觉感知中的同时应用。
Neighboring points on a smoothly curved surface have similar surface normals and illumination conditions. Therefore, their brightness values can be used to compute the ratio of their reflectance coefficients. Based on this observation, we develop an algorithm that estimates a reflectance ratio for each region in an image with respect to its background. The algorithm is efficient as it computes ratios for all image regions in just two raster scans. The region reflectance ratio represents a physical property that is invariant to illumination and imaging parameters. Several experiments are conducted to demonstrate the accuracy and robustness of ratio invariant.The ratio invariant is used to recognize objects from a single brightness image of a scene. Object models are automatically acquired and represented using a hash table. Recognition and pose estimation algorithms are presented that use ratio estimates of scene regions as well as their geometric properties to index the hash table. The result is a hypothesis for the existence of an object in the image. This hypothesis is verified using the ratios and locations of other regions in the scene. This approach to recognition is effective for objects with printed characters and pictures. Recognition experiments are conducted on images with illumination variations, occlusions, and shadows. The paper is concluded with a discussion on the simultaneous use of reflectance and geometry for visual perception.