A Novel Salient Region Detection Method Based on Hierarchical Spatial Information

被引:2
作者
Liu Shuo [1 ]
Ding Wenrui [2 ,3 ]
Li Hongguang [2 ]
Li Yingting [1 ]
机构
[1] Beihang Univ, Sch Elect & Informat Engn, Beijing 100191, Peoples R China
[2] Beihang Univ, Res Inst Unmanned Aerial Vehicle, Beijing 100191, Peoples R China
[3] Collaborat Innovat Ctr Geospatial Technol, Wuhan 430079, Peoples R China
基金
中国国家自然科学基金;
关键词
Salient region detection; Hierarchical spatial information; Compactness; Background possibility; VISUAL-ATTENTION; IMAGE; MODEL;
D O I
10.1049/cje.2017.01.027
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Different patterns in one object will cause unequal saliency degree which makes it hard to highlight the object region uniformly. We propose a salient region detection method which mainly includes image abstraction, saliency calculation and integration. Under the detection framework, the hierarchical spatial information is introduced to improve the performance. The image abstraction with "pixel level" spatial information is applied to capture some meaningful elements. The local contrast is calculated with the "element level" spatial information. The "object level" spatial information is represented as compactness and background possibility, which further help to better pop out the object region and suppress the background. The results show that our method has a good performance even though the object consists of complex patterns.
引用
收藏
页码:319 / 324
页数:6
相关论文
共 18 条
  • [1] SLIC Superpixels Compared to State-of-the-Art Superpixel Methods
    Achanta, Radhakrishna
    Shaji, Appu
    Smith, Kevin
    Lucchi, Aurelien
    Fua, Pascal
    Suesstrunk, Sabine
    [J]. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2012, 34 (11) : 2274 - 2281
  • [2] Achanta R, 2009, PROC CVPR IEEE, P1597, DOI 10.1109/CVPRW.2009.5206596
  • [3] [Anonymous], 2007, PROC IEEE C COMPUT V, DOI 10.1109/CVPR.2007.383267
  • [4] State-of-the-Art in Visual Attention Modeling
    Borji, Ali
    Itti, Laurent
    [J]. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2013, 35 (01) : 185 - 207
  • [5] Chen Z., 2013, CHINESE J ELECT, V22
  • [6] Efficient Salient Region Detection with Soft Image Abstraction
    Cheng, Ming-Ming
    Warrell, Jonathan
    Lin, Wen-Yan
    Zheng, Shuai
    Vineet, Vibhav
    Crook, Nigel
    [J]. 2013 IEEE INTERNATIONAL CONFERENCE ON COMPUTER VISION (ICCV), 2013, : 1529 - 1536
  • [7] Global Contrast based Salient Region Detection
    Cheng, Ming-Ming
    Zhang, Guo-Xin
    Mitra, Niloy J.
    Huang, Xiaolei
    Hu, Shi-Min
    [J]. 2011 IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR), 2011, : 409 - 416
  • [8] Saliency Detection in the Compressed Domain for Adaptive Image Retargeting
    Fang, Yuming
    Chen, Zhenzhong
    Lin, Weisi
    Lin, Chia-Wen
    [J]. IEEE TRANSACTIONS ON IMAGE PROCESSING, 2012, 21 (09) : 3888 - 3901
  • [9] FU Yi, 2008, MECH DESIGN, V04, P1
  • [10] Discriminant Saliency, the Detection of Suspicious Coincidences, and Applications to Visual Recognition
    Gao, Dashan
    Han, Sunhyoung
    Vasconcelos, Nuno
    [J]. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2009, 31 (06) : 989 - 1005