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Deep Learning and Approach for Tracking People’s Movements in a Video

机译:追踪人们在视频中移动的深度学习和方法

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摘要

Everyday, a large amount of data is produced thanks to technological advances in the field of multimedia, associated with the generalization of their use in many applications. The need to keep control over this content, in terms of data analysis, classification, accurate AI (Artificial Intelligence) algorithms are required to perform this task efficiently and quickly. In this article, we propose an approach using deep learning technologies for the analysis of movement in video sequences. The suggested approach uses images from video splitting to detect objects / entities present and store their descriptions in a standard XML file. As result, we provide a Deep Learning algorithm using TensorFlow for tracking motion and animated entities in video sequences.
机译:每天,由于多媒体领域的技术进步,与许多应用中使用的泛化相关联,产生了大量数据。在数据分析,分类,准确的AI(人工智能)算法方面需要保持控制的需要,以有效快速地执行此任务。在本文中,我们提出了一种利用深度学习技术来分析视频序列中的运动的方法。建议的方法使用来自视频拆分的图像来检测存在的对象/实体并将其描述在标准XML文件中。结果,我们提供了一种使用TensorFlow提供了一种深度学习算法,用于跟踪视频序列中的运动和动画实体。

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