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Application of virtual reality technology in multimedia resource with a focus on the COVID-19 outbreak
Journal of Commercial Biotechnology ; 27(1):181-189, 2022.
Article in English | EMBASE | ID: covidwho-2010466
ABSTRACT
In order to solve the problem of high energy consumption caused by unable to extract color space parameters in multimedia resource compression and transmission algorithm, the application of virtual reality technology in multimedia resource compression and transmission algorithm is studied. The pixels are classified according to labeled and unlabeled, the multimedia resource allocation strategy is established, the resource target area is extracted by virtual reality technology, and the over segmentation is controlled to a small extent, so as to control the quality of resources. In order to reduce the number of data transmission and reception in the process of data aggregation in the network, a transmission signal reconstruction model is constructed, and the data is compressed and encoded. A compression transmission algorithm is designed, which uses compressed sensing and network coding to reduce the amount of data transmission. The experimental results demonstrate that the energy consumption of the compression transmission algorithm proposed in this work increases the single hop distance with the slowest rate and is also the least energy-intensive. Taking the bit rate of 0.25bpp as an example, the maximum energy consumption of the algorithm is 3.89J, which is 4.97J and 2.45J less than the direct transmission algorithm and the centralized compression transmission algorithm, respectively. Therefore, the algorithm can reduce energy consumption and prolong the life cycle of transmission network.
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Full text: Available Collection: Databases of international organizations Database: EMBASE Type of study: Experimental Studies Language: English Journal: Journal of Commercial Biotechnology Year: 2022 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: EMBASE Type of study: Experimental Studies Language: English Journal: Journal of Commercial Biotechnology Year: 2022 Document Type: Article