计算机科学 ›› 2016, Vol. 43 ›› Issue (5): 269-273.doi: 10.11896/j.issn.1002-137X.2016.05.051
张红斌,姬东鸿,尹兰,任亚峰
ZHANG Hong-bin, JI Dong-hong, YIN Lan and REN Ya-feng
摘要: 提出为商品图像标注句子,以便更准确地刻画图像内容。首先,执行图像特征学习,选出标注性能最优的梯度核特征完成图像分类和图像检索,该特征能客观描绘商品图像中形状和纹理这两类关键视觉特性。然后,基于语义相关度计算结果从训练图像的文本描述中摘取关键单词,并采用N-gram模型把单词组装为蕴涵丰富语义信息且满足句法模式兼容性的修饰性短语,基于句子模板和修饰性短语生成句子。最后,构建Boosting模型,从若干标注结果中选取BLEU-3评分最优的句子标注商品图像。结果表明,Boosting模型的标注性能优于各基线。
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