An image-set for identifying multiple regions/levels of interest in digital images

摘要

In the field of identifying regions-of-interest (ROI) in digital images, several image-sets are referenced in the literature; the open-source ones typically present a single main object (usually located at or near the image center as a pop-out). In this paper, we present a comprehensive image-set (with its ground-truth) which will be made publically available. The database consists of images that demonstrate multiple-regions-of-interest (MROI) or multiple-levels-of-interest (MLOI). The former terminology signifies that the scene has a group of subjects/objects (not necessarily spatially-connected regions) that share the same level of perceptual priority to the human observer while the latter indicates that the scene is complex enough to have primary, secondary, and background objects. The methodology for developing the proposed image-set is described. A psychophysical experiment to identify MROI and MLOI was conducted, the results of which are also presented. The image-set has been developed to be used in training and evaluation of ROI detection algorithms. Applications include image compression, thumbnailing, summarization, and mobile phone imagery.