Video classification method and device and server

A video classification and classifier technology, which is applied in video data clustering/classification, video data retrieval, neural learning methods, etc., can solve problems such as single feature dimension and poor video classification effect, and achieve the effect of improving accuracy

Active Publication Date: 2019-02-19
TENCENT TECH (SHENZHEN) CO LTD
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  • Abstract
  • Description
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  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The embodiment of the present application provides a video classification method, device and server, which can solve the problem of poor video classification effect due to single feature dimension when video classification is based on image features

Method used

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  • Video classification method and device and server
  • Video classification method and device and server
  • Video classification method and device and server

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Embodiment Construction

[0035] In order to make the purpose, technical solution and advantages of the present application clearer, the implementation manners of the present application will be further described in detail below in conjunction with the accompanying drawings.

[0036] For the convenience of understanding, the nouns designed in the embodiments of the present application are described below.

[0037] Convolutional layer: It is composed of the weight and bias items of the convolution kernel. In a convolutional layer, the output of the previous layer (also known as the feature map) is convoluted by a convolution kernel, and the output feature map is obtained through an activation function. Among them, the feature map can be expressed as:

[0038]

[0039] in, Represents the weight parameter connecting the i unit of the l layer and the j unit of the l+1 layer, Is the parameter corresponding to the j unit connecting the l-th layer bias unit and the l+1 layer, FM l is the set of featu...

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Abstract

The invention discloses a video classification method and device and a server. The method comprises the following steps of: obtaining a target video; The image frames in the target video are classified by the first classification model, and the image classification result is obtained. The first classification model is used for classification based on the image features of the image frames. The audio in the target video is classified by the second classification model, and the audio classification result is obtained. The second classification model is used to classify the audio based on the audio features. The text description information corresponding to the target video is classified by the third classification model, and the text classification result is obtained. The third classification model is used to classify the text information based on the text characteristics of the text description information. According to the image classification results, audio classification results andtext classification results, the target video target classification results are determined. In the present application, image features, audio features and text features are integrated for classification, and features of different dimensions of the video are fully considered, thereby improving the accuracy of the video classification.

Description

technical field [0001] The embodiments of the present application relate to the field of video classification, and in particular to a video classification method, device and server. Background technique [0002] The recommendation function is a common function in video applications. It is used to recommend videos of interest to users, and the quality of the recommendation function is closely related to the accuracy of video classification. [0003] In related technologies, an image recognition-based method is used to classify videos. In a video classification method based on image recognition, by extracting the image frames in the video and extracting the image features of the image frames, the image features are input into the long short-term memory (Long Short-Term Memory, LSTM) according to the timing of the image frames. ) network, and then determine the video classification according to the output of the LSTM network. [0004] However, when video classification is bas...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06V10/764
CPCG06F16/75G06F16/7847G06F16/7844G06F16/7834G06N3/08G06N3/044G06N3/045G10L25/51G06F40/279G06F40/30G06V20/40G06V20/635G06V10/82G06V10/811G06V10/764G06F18/256Y02D10/00G10L25/24G10L25/57G06V20/41G06V20/46G06F18/22G06F18/2415G06F18/2431
Inventor 屈冰欣郑茂
Owner TENCENT TECH (SHENZHEN) CO LTD
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