Kinect vs Lytro in RGB-D Face Recognition

V. Chiesa, J. Dugelay
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引用次数: 2

Abstract

Light field cameras are becoming increasingly popular thanks to higher capabilities with respect to regular cameras in capturing information of a scene. Even though the principle associated with structured light sensors is quite different from the technology behind light field cameras, data provided by these technologies are similar in terms of depth map. With the aim of comparing the potential of Kinect and Lytro sensors on face recognition, two experiments are conducted on separate but publically available datasets and validated on a database acquired simultaneously with Lytro Illum camera and Kinect V1 sensor. The results obtained on RGB and depth maps are integrated with an experiment based on fusion at score level. The introduction of depth information in the RGB data is found more effective than standard bi dimensional imaging, especially in case of occlusions.
Kinect与Lytro在RGB-D人脸识别中的对比
由于在捕捉场景信息方面比普通相机具有更高的功能,光场相机正变得越来越受欢迎。尽管与结构光传感器相关的原理与光场相机背后的技术有很大不同,但这些技术提供的数据在深度图方面是相似的。为了比较Kinect和Lytro传感器在人脸识别方面的潜力,我们在独立但公开的数据集上进行了两个实验,并在Lytro Illum相机和Kinect V1传感器同时获取的数据库上进行了验证。在RGB图和深度图上得到的结果与基于分数水平融合的实验相结合。在RGB数据中引入深度信息比标准的二维成像更有效,特别是在遮挡的情况下。
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