Multi-label video classification method and system, system training method and device

A video classification and multi-label technology, applied in the direction of instrumentation, computing, character and pattern recognition, etc., can solve problems such as feature spaces that do not take into account the better initial feature space

Active Publication Date: 2021-08-20
BEIJING QIYI CENTURY SCI & TECH CO LTD
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AI Technical Summary

Problems solved by technology

[0006] The original video and audio features are directly used as the input of the aggregation operation NetVLAD, without considering whether the initial feature space is suitable for a better feature space for multi-label video classification problems

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  • Multi-label video classification method and system, system training method and device
  • Multi-label video classification method and system, system training method and device
  • Multi-label video classification method and system, system training method and device

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Embodiment Construction

[0192] The technical solutions in the embodiments of the present invention will be described below with reference to the drawings in the embodiments of the present invention.

[0193] The multi-label video classification technology based on the neural network model generally inputs the feature information of the video to be labeled into the trained neural network model, and then uses the neural network model to generate label information for the video. The public dataset YouTube-8M can be used for multi-label video classification by the existing Gated NetVLAD method.

[0194] YouTube-8M is currently the largest video dataset released by Google, which contains more than 7 million YouTube video data, corresponding to 4716 classification labels. Google also released the characteristics of these videos, including video and audio parts. The extraction process of video features is as follows: sampling an image every 1 second, accumulatively sampling 300 images, and then extracting ...

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Abstract

The embodiment of the present invention provides a multi-label video classification method and system, system training method and device, wherein the multi-label video classification method includes: acquiring the video to be processed, extracting the initial features of the video to be processed; extracting the extracted initial video feature matrix and The initial audio feature matrix is ​​transformed separately to generate a new video feature matrix and a new audio feature matrix; the new video feature matrix and the new audio feature matrix are aggregated to generate an aggregated feature vector; Process multiple classification labels of a video and the confidence corresponding to each classification label. The multi-label video classification method provided by the embodiment of the present invention can improve the accuracy of multi-label video classification.

Description

technical field [0001] The present invention relates to the technical field of multi-label video classification, in particular to a multi-label video classification method and system, and a system training method and device. Background technique [0002] With the development of Internet technology, more and more people choose to watch videos through the Internet. When displaying video information, the video playback website will display the classification label of the video, that is, the category to which the video belongs. Often, a video has more than one tag, for example, a video can have both a war tag and a sci-fi tag. Multi-label video classification can be achieved through neural network models. [0003] The multi-label video classification technology based on the neural network model generally inputs the feature information of the video to be labeled into the trained neural network model, and then uses the neural network model to generate label information for the v...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/00
CPCG06V20/41G06V20/46
Inventor 梁大为
Owner BEIJING QIYI CENTURY SCI & TECH CO LTD
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