Region Proposal-Based Convolutional Neural Network for Missing Child Detection

L. Rasikannan, J. Suganthi, R. Sasikumar, K. ReshmaV.
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Abstract

Object identification has exploded alongside the remarkable progression of Convolutional Neural Network and its variations since 2012. Identification of objects in a field of computer vision has significantly increased especially to face and human subjects. Subsequently, computer vision has also addressed a global challenge on certain systems such as missing child detection in the last decade. However, there are certain challenges and limitations in the detection of children in the crowd only with face detection. Thus this paper proposes a Regional proposal based Convolutional Neural Network system that addresses the global challenges using three add-on features along with face. The real time dataset has been collected and the experimentations are conducted to validate the significance of the proposed system.
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基于区域建议的卷积神经网络失踪儿童检测
自2012年以来,随着卷积神经网络及其变体的显著发展,物体识别也出现了爆炸式增长。在计算机视觉领域,对物体的识别有了显著的提高,尤其是对人脸和人类主体的识别。随后,在过去十年中,计算机视觉也解决了某些系统的全球挑战,例如失踪儿童检测。然而,仅用人脸检测在人群中检测儿童存在一定的挑战和局限性。因此,本文提出了一种基于区域建议的卷积神经网络系统,该系统使用三个附加特征和人脸来解决全球挑战。通过对实时数据集的采集和实验,验证了该系统的有效性。
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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