[1]严 晗,刘佶鑫,龚建荣.典型室内场景显著性稀疏识别[J].南京师范大学学报(自然科学版),2017,40(01):79.[doi:10.3969/j.issn.1001-4616.2017.01.012]
　Yan Han,Liu Jixin,Gong Jianrong.Significant Spare Representation of Typical Indoor Scene Recognition[J].Journal of Nanjing Normal University(Natural Science Edition),2017,40(01):79.[doi:10.3969/j.issn.1001-4616.2017.01.012]
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典型室内场景显著性稀疏识别()
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《南京师范大学学报》（自然科学版）[ISSN:1001-4616/CN:32-1239/N]

卷:
第40卷
期数:
2017年01期
页码:
79
栏目:
·数学与计算机科学·
出版日期:
2017-03-31

文章信息/Info

Title:
Significant Spare Representation of Typical Indoor Scene Recognition
文章编号:
1001-4616(2017)01-0079-07
作者:
严 晗1; 刘佶鑫2; 龚建荣2
(1.南京邮电大学通信与信息工程学院,江苏 南京 210003)(2.南京邮电大学教育部工程研究中心,江苏 南京 210003)
Author(s):
Yan Han1; Liu Jixin2; Gong Jianrong2
(1.College of Telecommunication and Information Engineering,Nanjing University of Posts and Telecommunications,Nanjing 210003,China)(2.Engineering Research Center of Education,Nanjing University of Posts and Telecommunications,Nanjing 210003,China)
关键词:
场景识别; 室内场景分类; 显著性区域检测; 稀疏表示
Keywords:
scene recognition; indoor scene classification; salient region detection; sparse representation
分类号:
TP391
DOI:
10.3969/j.issn.1001-4616.2017.01.012
文献标志码:
A
摘要:
随着信息技术和智能机器人的发展与普及,场景识别作为重要的研究内容,已成为计算机视觉和模式识别领域的重要研究问题. 解决室内场景分类精度低的问题,将有助于室内场景分类在场景图片检索、视频检索及机器人等领域中的应用. 针对常规场景识别方法在室内环境中性能显著下降的问题,提出一种基于显著性检测的稀疏表示室内场景识别方法. 该方法利用显著性区域检测算法提取出场景图像中人眼感兴趣的区域,并与稀疏表示结合进行场景识别. 实验结果表明,将本方法应用在典型家庭室内场景(如卧室、厨房、衣帽间等),在识别正确率方面有一定的优势.
Abstract:
With the development and popularization of information technology and intelligent robots,scene recognition as an important research content has become an important research in the field of computer vision and pattern recognition problem. Solving the problem of the low classification accuracy for indoor scene will help the indoor scene classification in some areas of application:the image retrieval,video retrieval of the scene and the robot. Conventional scene recognition methods have poor performance in indoor situations. For this reason,a sparse representation indoor scene recognition method is presented,which based on significant detection. This method is using significant recognition detection to extract the scene in the image area which we are interested in,and combined with sparse representation to scene classification recognition. Experimental results show that this method can be applied to a typical family indoor scenarios(e.g.,bedroom,kitchen,closet,etc.)and have certain advantages in terms of recognition accuracy.

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备注/Memo

备注/Memo:
收稿日期:2016-08-20.
基金项目:国家自然科学基金青年基金(61401220)、江苏省自然科学基金青年基金(BK20140884)、江苏省高校自然科学研究面上项目(14KJB510022).
通讯联系人:严晗,硕士,研究方向:稀疏表示、图像处理. E-mail:729838449@qq.com
更新日期/Last Update: 1900-01-01