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IMAGE CONTENT AUTOMATIC DESCRIPTION METHOD BASED ON CONSTRUCTION OF CHINESE VISUAL VOCABULARY LIST

机译:基于汉语视觉词汇表的图像内容自动描述方法

摘要

Provided is an image content automatic description method based on the construction of a Chinese visual vocabulary list. The method comprises steps performed in order: step a, using a Chinese word segmentation tool to perform word segmentation processing on several descriptive sentences corresponding to a single picture, selectively reserving nouns, verbs and adjectives in a word list according to statistical word frequencies, and then using the reserved words to form a Chinese visual vocabulary list; step b, carrying out prediction on the Chinese visual vocabulary list on the basis of a Chinese vocabulary list prediction network, to obtain image label information; and step c, on the basis of an automatic image description model, using an encoder to extract image convolutional features, and then using a decoder to decode the image convolutional features, as an initial input, into a Chinese descriptive statement. Image label information can be obtained by carrying out prediction on an image vocabulary list on the basis of a vocabulary list prediction network, and a residual structure is added to a Chinese visual vocabulary list prediction network, such that the problem of network degradation along with an increase in the number of layers of a Chinese visual vocabulary list prediction network can be effectively solved.
机译:提供了一种基于中文视觉词汇表的构建的图像内容自动描述方法。该方法包括按顺序执行的步骤:步骤a,使用汉字分段工具对与单个图片相对应的若干描述性句子执行词分割处理,根据统计字频率选择性地保留单词列表中的名词,动词和形容词,然后使用保留的单词形成中文视觉词汇表;步骤B,在中国词汇列表预测网络的基础上对中文视觉词汇列表进行预测,以获取图像标签信息;和步骤C,基于自动图像描述模型,使用编码器提取图像卷积特征,然后使用解码器将图像卷积特征作为初始输入解码为中文描述性语句。图像标签信息可以通过在词汇列表预测网络的基础上对图像词汇表列表进行预测来获得,并且将残余结构添加到中文视觉词汇列表预测网络,使得网络劣化问题以及一个可以有效解决中文视觉词汇列表预测网络的层数的增加。

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