基于相对视觉显著性的人脸注意力引导新方法

R. Kumar, Jogendra Garain, G. Sanyal, D. Kisku
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引用次数: 3

摘要

在拥挤的人群中识别人脸在监测中起着重要作用。人脸识别在不同的应用领域已经进行了大量的研究。因此,不同的研究者提出了新的算法。本文试图展示一种新的方法,通过这种方法可以在大量人脸中识别任何人脸。该技术基于相对视觉显着性,该显着性是根据人脸的强度值和各自的空间距离来评估的。除了视觉显著性,自上而下和自下而上的视觉注意方法也在人脸识别的背景下提出和解释。这两种方法都被认为对基于注意力的人脸识别做出了重大贡献,而视觉显著性是基于注意力的人脸识别的测量方法。在测试图像数据集上进行了实验。结果令人满意,并测量了精度。用该方法进行的评估显示出相当令人鼓舞的结果和准确性,为未来的人脸跟踪和识别系统模型奠定了基础。
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Novel methodology for guiding attention of faces through relative visual saliency (RVS)
Identification of a human face in a crowded flux plays an important role in the context of surveillance. Considerable amount of research has been carried out on face identification in different applications. Accordingly, different researchers propose new algorithms. This paper attempts to showcase a novel methodology through which any face may be identified in a large crowd of human face. This proposed technique is based on relative visual saliency which is evaluated on the intensity values and respective spatial distance of the faces. In addition to visual saliency, top-down and bottom-up approaches to visual attention are also presented and explained in the context of face identification. Both of these two approaches are considered to be made a significant contribution while visual saliency is measured for attention-based face identification. Experiment has been carried out on test image dataset. The results are satisfactory and accuracy has also been measured. The evaluation made with the proposed approach exhibits quite encouraging results and accuracy leads to a future model of human face tracking and recognition system.
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