Abstract
With the development of information technology and multimedia technology, a short video to become a user preferences, due to the long short and large amount of information become the user to be bestowed favor on newly, in order to find out from thousands of video two similar video, traditional approach is to extract the corresponding characteristic in the video, such as color, texture, gray level and other characteristics, and create the corresponding data index, Then put to query to extract the corresponding 3 d video features and compare the features in the database, so as to find the most similar 3 d video, the traditional way of data information is two-dimensional video is used, but in the data information of very large 3 d video efficiency and the effect is greatly reduced, and the results will greatly reduce the efficiency of the traditional data retrieval, Here, the method of principal component analysis without supervision problem is used to reduce the dimension of 3d video information, which can reduce the dimension from 128 to 64, thus greatly improving the efficiency of 3D video retrieval. Experimental results show that the method of principal component analysis for 3d data dimensionality reduction can greatly improve the efficiency of video retrieval.
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Jia, S., Yang, T., Sui, Z. (2022). Research on Application of Principal Component Analysis in 3d Video Dimension Reduction. In: Sun, X., Zhang, X., Xia, Z., Bertino, E. (eds) Artificial Intelligence and Security. ICAIS 2022. Lecture Notes in Computer Science, vol 13339. Springer, Cham. https://doi.org/10.1007/978-3-031-06788-4_2
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