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首页> 外文会议>Portland International Conference on Management of Engineering and Technology >Data Storage Cost Reduction by Decluttering Image and Video Data: Case Study of Video File Decluttering
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Data Storage Cost Reduction by Decluttering Image and Video Data: Case Study of Video File Decluttering

机译：通过整理图像和视频数据减少数据存储成本：视频文件展示的案例研究

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Big Data growth does not stop. Companies are forced to store data without knowing its value or usage because data has potential to become next revenue opportunity. Since the cost for storing data increases as the amount of data grows, efficient data storage methods are required. We introduce a method to reduce the cost of data storage by partial decluttering of image and video data. In our method, only the portions of image or video files containing recognized objects are extracted. This is based on the assumption that images of objects of interest may be used in the future, but other image data, such as the background, can be discarded. We use the neural network computer stick from Intel Corporation to accelerate the computation. In the case study of a video file, our method successfully reduced the data size by approximately 50% on average. In addition to that, we realized a low-cost method that can be applied not only to large companies but also small to medium companies by using a low cost hardware accelerated implementation. We interviewed experts in corporate IT data management and qualitatively demonstrated that our method is valuable and eflective. Our research has contributed to IT managements' decision-making support to resolve their data storage vs. cost problem.
机译：大数据增长不会停止。公司被迫存储数据而不知道其价值或使用，因为数据有可能成为下一步收入机会。由于存储数据的成本随着数据量而增加，因此需要有效的数据存储方法。我们介绍了一种通过图像和视频数据的部分倾斜来降低数据存储成本的方法。在我们的方法中，仅提取包含识别对象的图像或视频文件的部分。这是基于假设，未来可以使用感兴趣对象的图像，但是可以丢弃其他图像数据，例如背景。我们使用来自英特尔公司的神经网络计算机杆加速计算。在对视频文件的情况下，我们的方法平均成功将数据大小降低了大约50±％。除此之外，我们还实现了一种低成本的方法，不仅可以应用于大公司，也可以使用低成本硬件加速实现来应用于中等公司。我们采访了企业IT数据管理的专家，并定性证明了我们的方法是有价值的和效果。我们的研究促成了IT管理层的决策支持，以解决其数据存储与成本问题。

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