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Robust and scalable aggregation of local features for ultra large-scale retrieval

Husain, Syed and Bober, Miroslaw (2014) Robust and scalable aggregation of local features for ultra large-scale retrieval In: nternational Conference on Image Processing (ICIP), Paris, 2014, 27-30 October 2014, Paris.

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This paper is concerned with design of a compact, binary and scalable image representation that is easy to compute, fast to match and delivers beyond state-of-the-art performance in visual recognition of objects, buildings and scenes. A novel descriptor is proposed which combines rank-based multi-assignment with robust aggregation framework and cluster/bit selection mechanisms for size scalability. Extensive performance evaluation is presented, including experiments within the state-of-the art pipeline developed by the MPEG group standardising Compact Descriptors for Visual Search (CVDS).

Item Type: Conference or Workshop Item (Conference Paper)
Divisions : Faculty of Engineering and Physical Sciences > Electronic Engineering > Centre for Vision Speech and Signal Processing
Authors :
Date : 27 October 2014
DOI : 10.1109/ICIP.2014.7025566
Related URLs :
Depositing User : Miroslaw Bober
Date Deposited : 20 Mar 2015 10:36
Last Modified : 06 Jul 2019 05:14

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