Research Article
A Video Parallel Retrieval Method Based on Deep Hash
6 downloads
@INPROCEEDINGS{10.1007/978-3-030-97124-3_12, author={Jiayi Li and Lulu Bei and Dan Li and Ping Cui and Kai Huang}, title={A Video Parallel Retrieval Method Based on Deep Hash}, proceedings={Simulation Tools and Techniques. 13th EAI International Conference, SIMUtools 2021, Virtual Event, November 5-6, 2021, Proceedings}, proceedings_a={SIMUTOOLS}, year={2022}, month={3}, keywords={Deep hash Convolution neural network High precision}, doi={10.1007/978-3-030-97124-3_12} }- Jiayi Li
Lulu Bei
Dan Li
Ping Cui
Kai Huang
Year: 2022
A Video Parallel Retrieval Method Based on Deep Hash
SIMUTOOLS
Springer
DOI: 10.1007/978-3-030-97124-3_12
Abstract
This paper designs a parallel video retrieval based on Spark and deep hash. The method comprises deep feature extraction using a convolution neural network based on partial semantic weighted aggregation; filtering features of image information in deep networks; the extraction and distributed storage of video summary keys; the establishment of distributed product quantitative hash coding model of image, realizing the distributed coding compression of high-dimensional features. The video parallel retrieval method proposed in this design has the advantages of high retrieval accuracy and good retrieval efficiency.
Copyright © 2021–2025 ICST
