静态图像行为标注众包系统的设计与实现

摘要/Abstract

摘要： 针对静态图像行为识别研究缺乏标注数据的问题,在Android平台下,利用“众包”思想,设计并开发了基于静态图像的视觉行为人工标注系统。该系统主要包括分配标注任务、用户标注图像信息、评审标注信息和查看历史标注信息等功能。对于评审分数较高的标注信息,利用网络爬虫技术提取该图像的辅助文本标签,并且将标注信息转化为词向量后进行存储,以便于后期的实验研究。同时,系统应用一种基于定价机制的任务分配算法,有效地提高了用户图像标注效率。实际部署系统应用情况表明,该系统操作简洁、流畅,各算法功能模块稳定、高效,并且充分地利用移动端便捷的优势,能够顺利进行图像行为标注数据的收集和整理工作。

关键词: Android, 词向量, 图像行为标注, 网络爬虫, 众包

Abstract: According to the problem of lack of the annotation data in still image activity recognition research,under the Android platform,a visual activity manual annotation system based on still images was designed and developed with the idea of “crowd-sourcing”.The system mainly includes the functions of assigning annotation tasks,annotating image information,reviewing annotation information and examining historical annotation information.For the annotation information with high evaluation scores,the web crawler technology is used to extract the auxiliary text labels of the image,and the annotation information is converted into word embedding storage for the convenience of later experimental research.Meanwhile,the system applies a task assignment algorithm based on pricing mechanism,which effectively improves the efficiency of user image annotation.The application of the actual deployment system shows that the operation is simple and smooth,the function modules of each algorithm are stable and efficient,and the advantages of mobile terminals are fully utilized to collect and organize the data of image activity annotation.

Key words: Android, Crowdsourcing, Image activity annotation, Web crawler, Word embedding

中图分类号:

TP311.52

侯禹臣, 吴伟. 静态图像行为标注众包系统的设计与实现[J]. 计算机科学, 2019, 46(11A): 580-583. https://doi.org/

HOU Yu-chen, WU Wei. Design and Implementation of Crowdsourcing System for Still Image Activity Annotation[J]. Computer Science, 2019, 46(11A): 580-583. https://doi.org/

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