Learning multiple local binary descriptors for image matching.

	Learning multiple local binary descriptors for image matching.
	Gao, Yongqian ; Huang, Weilin ; Qiao, Yu
刊名	NEUROCOMPUTING
	2017
文献子类	期刊论文
英文摘要	Binary descriptors have received extensive research interests due to their low memory storage and computational efficiency. However, the discriminative ability of the binary descriptors is often limited in comparison with general floating point ones. In this paper, we present a learning framework to effectively integrate multiple binary descriptors, which is referred as learning-based multiple binary descriptors (LMBD). We observe that previous successful binary descriptors like Receptive Fields Descriptor (RFD) which includes rectangular pooling area (RFDR) and Gaussian pooling area (RFDG)), BinBoost, and Boosted Gradient Maps (BGM), are highly complementary to each other. We show that the proposed LMBD can improve the discriminative ability of individual binary descriptorssignificantly. We formulate the fusion of multiple groups of the binary descriptors was formulated as a pair-wise ranking problem, which can be solved effectively in a rankSVM framework. Extensive experiments were conducted to evaluate the efficiency of LMBD. The proposed LMBD obtains the error rate of 12.44% on the challenging local patch datasets, which is about 2% lower than the state-of-the-art results (obtained by a learning based floating point descriptor). Furthermore, the proposed binary descriptor also outperforms other binary descriptors on image matching task.
URL标识	查看原文
语种	英语
内容类型	期刊论文
源URL	[http://ir.siat.ac.cn:8080/handle/172644/11563]
专题	深圳先进技术研究院_集成所
作者单位	NEUROCOMPUTING
推荐引用方式 GB/T 7714	Gao, Yongqian , Huang, Weilin , Qiao, Yu. Learning multiple local binary descriptors for image matching.[J]. NEUROCOMPUTING,2017.
APA	Gao, Yongqian , Huang, Weilin ,& Qiao, Yu.(2017).Learning multiple local binary descriptors for image matching..NEUROCOMPUTING.
MLA	Gao, Yongqian ,et al."Learning multiple local binary descriptors for image matching.".NEUROCOMPUTING (2017).