Multiple Query Content-Based Image Retrieval Using Relevance Feature Weight Learning

Abeer Al-Mohamade, Ouiem Bchir, Mohamed Maher Ben Ismail
2020 Journal of Imaging  
We propose a novel multiple query retrieval approach, named weight-learner, which relies on visual feature discrimination to estimate the distances between the query images and images in the database. For each query image, this discrimination consists of learning, in an unsupervised manner, the optimal relevance weight for each visual feature/descriptor. These feature relevance weights are designed to reduce the semantic gap between the extracted visual features and the user's high-level
more » ... cs. We mathematically formulate the proposed solution through the minimization of some objective functions. This optimization aims to produce optimal feature relevance weights with respect to the user query. The proposed approach is assessed using an image collection from the Corel database.
doi:10.3390/jimaging6010002 pmid:34460641 fatcat:smvddgbhqvdpfd4oiopu2irihy