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Received:March 25, 2019 Revised:April 18, 2019
Received:March 25, 2019 Revised:April 18, 2019
中文摘要: 目标检测广泛使用于计算机视觉领域.在不同的场景中，我们需要使用不同的数据集训练模型.但是，人工生成数据集标签非常耗时.本文提出一种半自动的方法生成数据集标签，然后按照图像相似度设置的阈值自动筛选，最后保留符合要求的图像和对应的标签作为最终的数据集.实验表明，该方法可以提高数据集生成标签的速度，同时确保了准确率.
Abstract:Object detection is widely used in the field of computer vision. In different occasions, we need to use different training set to train the model. However, manually generating label is very time consuming. This study proposed a semi-automatic method to generate labels for dataset, then automatically filter them according to the threshold set by image similarity, lastly retain the required images and corresponding labels as the final dataset. Experiments show that the method can both improve the speed and ensure accuracy rate of generating labels for dataset.
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基金项目:中国科学院科技服务网络计划（KFJ-STS-QYZD-058）
引用文本：
孙晓璇,张磊,李健.目标检测数据集半自动生成技术研究.计算机系统应用,2019,28(10):8-14
SUN Xiao-Xuan,ZHANG Lei,LI Jian.Research on Semi-Automatic Generation Technology of Object Detection Datasets.COMPUTER SYSTEMS APPLICATIONS,2019,28(10):8-14
孙晓璇,张磊,李健.目标检测数据集半自动生成技术研究.计算机系统应用,2019,28(10):8-14
SUN Xiao-Xuan,ZHANG Lei,LI Jian.Research on Semi-Automatic Generation Technology of Object Detection Datasets.COMPUTER SYSTEMS APPLICATIONS,2019,28(10):8-14
