Spatial relationship recognition via heterogeneous representation: A review

Authors：Wang, Yang^*; Peng, Huilin; Xiong, Yiwei; Song, Haitao

Source：NEUROCOMPUTING, 2023, 533: 116-140.

DOI：10.1016/j.neucom.2023.02.053

• Spatial relationship recognition
• Spatial representation
• Spatial descriptor
• Relation graph

Spatial relationship between objects in an image can help to gain a deep understanding of the image. At present, spatial relationship recognition has received more and more attentions and has been applied to many computer vision tasks. Although many substantial studies have been continuing, there is few review for investigating spatial relationship recognition. Therefore, we make this comprehensive survey that covers major literatures in spatial relationship recognition. Especially, we focus on spatial description which occurs in forms of spatial descriptors, definitional descriptions, probabilistic descriptions, and model descriptions. We analyse its impacts on the state-of-the-art research on spatial relationship recognition in recent years. In this survey, we introduce a classification of methodologies, and show strengths and weaknesses of methods in each category. Besides, we compare the performance of methods and algorithms most of which are learning styled and based on popular public datasets. In addition, many future research directions are also discussed, such as technology trends, and dataset creation, etc.

• Institution
  y; 上海交通大学