Object recognition based on reconstruction of light field

Guangfu Zhou, Chenglin Wen, Jingli Gao
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引用次数: 1

Abstract

With the rapid development of modern information technology, target recognition plays an increasingly important role in agricultural production, national defense construction. However, the existing target recognition algorithm has many limitations, such as image distortion, difficult to recognize target image or poor recognition results because of camera angles and lighting conditions. Based on the above questions, the paper proposes an image recognition algorithm, and the light field is applied to the image recognition as the feature extraction library for first time. First, we obtain light field information which contains images taken from different angles of the target object, and then regard the light field information as an object library. Finally we perform the algorithm of target recognition for the target image based on the object library. Based on sparse Fourier transform, the light field reconstruction algorithm in this paper can reconstruct the entire light field with a small amount of samples. This recognition algorithm can solve the problem to recognize image due to the different camera angles. Finally, the simulation verifies the effectiveness of the algorithm.
基于光场重建的目标识别
随着现代信息技术的飞速发展,目标识别在农业生产、国防建设等方面发挥着越来越重要的作用。然而,现有的目标识别算法存在许多局限性,如受相机角度和光照条件的影响,图像失真,目标图像难以识别或识别效果不佳。针对上述问题,本文提出了一种图像识别算法,并首次将光场作为特征提取库应用到图像识别中。首先,我们获得包含目标物体不同角度图像的光场信息,然后将光场信息作为一个目标库。最后对目标图像进行基于目标库的目标识别算法。本文提出的基于稀疏傅里叶变换的光场重建算法,可以用少量的样本重建整个光场。该识别算法可以很好地解决由于相机角度不同而导致的图像识别问题。最后通过仿真验证了算法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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