21 July 2017 Multi-instance learning based on instance consistency for image retrieval
Author Affiliations +
Proceedings Volume 10420, Ninth International Conference on Digital Image Processing (ICDIP 2017); 104204J (2017) https://doi.org/10.1117/12.2281540
Event: Ninth International Conference on Digital Image Processing (ICDIP 2017), 2017, Hong Kong, China
Abstract
Multiple-instance learning (MIL) has been successfully utilized in image retrieval. Existing approaches cannot select positive instances correctly from positive bags which may result in a low accuracy. In this paper, we propose a new image retrieval approach called multiple instance learning based on instance-consistency (MILIC) to mitigate such issue. First, we select potential positive instances effectively in each positive bag by ranking instance-consistency (IC) values of instances. Then, we design a feature representation scheme, which can represent the relationship among bags and instances, based on potential positive instances to convert a bag into a single instance. Finally, we can use a standard single-instance learning strategy, such as the support vector machine, for performing object-based image retrieval. Experimental results on two challenging data sets show the effectiveness of our proposal in terms of accuracy and run time.
© (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Miao Zhang, Zhize Wu, Shouhong Wan, Lihua Yue, Bangjie Yin, "Multi-instance learning based on instance consistency for image retrieval", Proc. SPIE 10420, Ninth International Conference on Digital Image Processing (ICDIP 2017), 104204J (21 July 2017); doi: 10.1117/12.2281540; https://doi.org/10.1117/12.2281540
PROCEEDINGS
5 PAGES


SHARE
RELATED CONTENT

Efficient image retrieval with multiple distance measures
Proceedings of SPIE (January 15 1997)
Content-based image retrieval with scale-space object trees
Proceedings of SPIE (December 23 1999)
Object recognition and matching for image retrieval
Proceedings of SPIE (July 31 2002)
2+2=5: painting by numbers
Proceedings of SPIE (January 16 2006)
Warped metrics for image similarity retrieval
Proceedings of SPIE (December 20 2001)

Back to Top