{"type":"ScholarlyArticle","title":"A Novel Feature Matching Strategy for Large Scale Image Retrieval","authors":[{"name":"Hao Tang","slug":"hao-tang","given":"Hao","family":"Tang","affiliation":""},{"name":"Hong Liu","slug":"hong-liu-2","given":"Hong","family":"Liu","affiliation":""}],"abstract":"Feature-to-feature matching is the key issue in the Bag-of-Features model.The baseline approach employs a coarse feature-to-feature matching, namely, two descriptors are assumed to match if they are assigned the same quantization index.However, this Hard Assignment strategy usually incurs undesirable low precision.To fix it, Multiple Assignment and Soft Assignment are proposed.These two methods reduce the quantization error to some extent, but there are still a lot of room for improvement.To further improve retrieval precision, in this paper, we propose a novel feature matching strategy, called local-restricted Soft Assignment (lrSA), in which a new feature matching function is introduced.The lrSA strategy is evaluated through extensive experiments on five benchmark datasets.Experiments show that the results exceed the retrieval performance of current quantization methods on these datasets.Combined with post-processing steps, we have achieved competitive results compared with the state-of-the-art methods.Overall, our strategy shows notable benefit for retrieval with large vocabularies and dataset size.","doi":null,"url":"https://ijcai.org/proceedings/2016/293","pdf":"https://ijcai.org/proceedings/2016/0293.pdf","markdown":"https://ijcai.org/proceedings/2016/293.md","bibtex":"https://ijcai.org/proceedings/2016/bibtex/293","volume":{"slug":"2016","title":"Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2016","url":"https://ijcai.org/proceedings/2016/","year":2016,"location":"New York, NY, USA","dates":"9–15 July 2016","editors":"Subbarao Kambhampati","isbn":"978-1-57735-770-4; 978-1-57735-771-1","publisher":"AAAI Press / International Joint Conferences on Artificial Intelligence","doi_prefix":""},"section":null,"track":"","number":293,"pages":{"first":2053,"last":2058},"keywords":[],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}