There are plenty of places like home: Using relational representations in hierarchies for distance-based image understanding

NEUROCOMPUTING

卷:123

Article; Proceedings Paper

Antanas, Laura¹  van Otterlo, Martijn²  Mogrovejo, Jose Oramas³  Tuytelaars, Tinne³  De Raedt, Luc¹ 

[1] Katholieke Univ Leuven, Dept Comp Sci, B-3001 Heverlee, Belgium

[2] Radboud Univ Nijmegen, NL-6525 ED Nijmegen, Netherlands

[3] Katholieke Univ Leuven, Dept Elect Engn, Louvain, Belgium

关键词: Relational representations;    Relational instance-based learning;    Hierarchical image understanding;   

DOI  :  10.1016/j.neucom.2012.10.037

来源: Elsevier

【 摘 要 】

Understanding images in terms of logical and hierarchical structures is crucial for many semantic tasks, including image retrieval, scene understanding and robotic vision. This paper combines robust feature extraction, qualitative spatial relations, relational instance-based learning and compositional hierarchies in one framework. For each layer in the hierarchy, qualitative spatial structures in images are detected, classified and then employed one layer up the hierarchy to obtain higher-level semantic structures. We apply a four-layer hierarchy to street view images and subsequently detect corners, windows, doors, and individual houses. (C) 2013 Elsevier B.V. All rights reserved.

【 授权许可】

Free