Recognition of individual object in focus people group based on deep learning

Liu Hui-bin, Wu Fei, Chen Qiang, Pan Yong
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引用次数: 3

Abstract

Deep leaning has become a hot research topic with the rapid development of big data technology. As an important branch of deep learning, convolutional neural network has been widely used in image recognition, and has achieved great success. Convolutional architecture for fast feature embedding (Caffe) with features like speed, extendibility and openness is currently top popular tool of deep learning. In this paper, the authors use Caffe to realize the recognition of individual object in a focus people group. The training images can be obtained from the video recorded by the camera through the method of normalized cross-correlation histogram. The experimental results show that the individual object can be matched accurately by using pre training model. It can be used in practical work like attendance system, criminal investigation field etc.
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基于深度学习的焦点人群个体目标识别
随着大数据技术的飞速发展,深度学习已经成为一个热门的研究课题。卷积神经网络作为深度学习的一个重要分支,在图像识别中得到了广泛的应用,并取得了巨大的成功。卷积快速特征嵌入架构(Caffe)具有速度、可扩展性和开放性等特点,是目前最受欢迎的深度学习工具。在本文中,作者利用Caffe实现了焦点人群中单个对象的识别。通过归一化互相关直方图的方法从摄像机录制的视频中获得训练图像。实验结果表明,使用预训练模型可以准确匹配单个目标。它可以应用于考勤系统、刑侦领域等实际工作中。
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