首页> 外文期刊>Multimedia Systems >Decomposed human localization from social photo album
【24h】

Decomposed human localization from social photo album

机译:从社交相册分解人类本地化

获取原文
获取原文并翻译 | 示例
       

摘要

Recent years, there has tremendous progress in human detection, whereas only upright poses are usually considered, but the body poses in our daily lives are varied. In this paper, we mainly focus on localizing highly deformable persons which commonly appears in personal photo albums. Decomposition-based human localization is extremely challenging, due to the large pose variances, disabling the traditional part-based template detectors. To deal with the infeasibility of the template-based person models, we propose a decomposition-based human localization model based on the observation that highly deformable persons usually have a distinct body part (upper body) that possesses rigid and highly detectable structural nature, while the rest parts of the human are discriminative yet dependent to the upper body. The model tackles persons with highly deformable in three steps: firstly detect a stable upper body, then extend a set of bigger bounding boxes, from which the most appropriate instance is distinguished by a discriminative Whole Person Model (WPModel). From the experiment results, we can see that our decomposition-based model worked very well in localizing deformable persons, which improved the average precision by 10 % compared to state-of-the-art person detectors. And furthermore, Similar Pose Feature (SPF) shows the feasibility of projecting persons having similar poses into same clusters which facilitate a novel pose-based photo album browsing functionality.
机译:近年来,人体检测技术取得了长足进步,而通常只考虑直立姿势,但我们日常生活中的身体姿势却千差万别。在本文中,我们主要集中于定位经常出现在个人相册中的高度易变形的人。由于存在较大的姿势差异,因此基于分解的人体定位极具挑战性,从而使传统的基于零件的模板检测器无法使用。为了解决基于模板的人模型的不可行性,我们基于高度可变形的人通常具有明显的身体部位(上半身),具有刚性且高度可检测的结构性质,从而提出了基于分解的人体定位模型人的其余部分是有区别的,但取决于上身。该模型分三个步骤处理高度易变形的人:首先检测一个稳定的上身,然后扩展一组更大的边界框,通过判别性全人模型(WPModel)来区分最合适的实例。从实验结果可以看出,我们的基于分解的模型在定位可变形人员方面非常有效,与最新的人员检测器相比,其平均精度提高了10%。而且,相似姿势特征(SPF)显示了将具有相似姿势的人投影到相同集群中的可行性,这有助于新颖的基于姿势的相册浏览功能。

著录项

  • 来源
    《Multimedia Systems》 |2016年第1期|137-148|共12页
  • 作者单位

    Xiamen Univ, Dept Cognit Sci, Xiamen, Fujian, Peoples R China|Xiamen Univ, Fujian Key Lab, Brain Intelligent Syst, Xiamen 361005, Fujian, Peoples R China;

    Xiamen Univ, Dept Cognit Sci, Xiamen, Fujian, Peoples R China|Xiamen Univ, Fujian Key Lab, Brain Intelligent Syst, Xiamen 361005, Fujian, Peoples R China;

    Xiamen Univ, Dept Cognit Sci, Xiamen, Fujian, Peoples R China|Xiamen Univ, Fujian Key Lab, Brain Intelligent Syst, Xiamen 361005, Fujian, Peoples R China;

    Nanyang Technol Univ, Sch Elect & Elect Engn, Singapore 639798, Singapore;

    Xiamen Univ, Dept Cognit Sci, Xiamen, Fujian, Peoples R China|Xiamen Univ, Fujian Key Lab, Brain Intelligent Syst, Xiamen 361005, Fujian, Peoples R China;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Human detection; Decomposition-based human localization; Similar pose retrieval; Image browsing; Big data;

    机译:人体检测;基于分解的人体定位;相似姿态检索;图像浏览;大数据;
  • 入库时间 2022-08-18 02:06:02

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号