A Rule-based approach for detection of spatial object relations in images

Deep learning and Computer vision are becoming a part of everyday objects and machines. Involvement of artificial intelligence in human’s daily life open doors to new opportunities and research. This involvement provides the idea of improving upon the in-hand research of spatial relations and coming up with a more generic and robust algorithm that provides us with 2-D and 3-D spatial relations and uses RGB and RGB-D images which can help us with few complex relations such as ‘on’ or ‘in’ as well. Suggested methods are tested on the dataset with animated and real objects, where the number of objects varies in every image from at least 4 to at most 10 objects. The size and orientation of objects are also different in every image.