{"type":"ScholarlyArticle","title":"Learning Cross-View Binary Identities for Fast Person Re-Identification","authors":[{"name":"Feng Zheng","slug":"feng-zheng","given":"Feng","family":"Zheng","affiliation":""},{"name":"Ling Shao","slug":"ling-shao","given":"Ling","family":"Shao","affiliation":""}],"abstract":"In this paper, we propose to learn cross-view binary identities (CBI) for fast person re-identification. To achieve this, two sets of discriminative hash functions for two different views are learned by simultaneously minimising their distance in the Hamming space, and maximising the cross-covariance and margin. Thus, similar binary codes can be found for images of a same person captured at different views by embedding the images into the Hamming space. Therefore, person re-identification can be solved by efficiently computing and ranking the Hamming distances between the images. Extensive experiments are conducted on two public datasets and CBI produces comparable results as state-ofthe- art re-identification approaches but is at least 2200 times faster.","doi":null,"url":"https://ijcai.org/proceedings/2016/342","pdf":"https://ijcai.org/proceedings/2016/0342.pdf","markdown":"https://ijcai.org/proceedings/2016/342.md","bibtex":"https://ijcai.org/proceedings/2016/bibtex/342","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":342,"pages":{"first":2399,"last":2405},"keywords":[],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}