Domain-Size Pooling in Local Descriptors: DSP-SIFT

被引：0

作者：

Dong, Jingming ^{[1
]}

Soatto, Stefano ^{[1
]}

机构：

[1] Univ Calif Los Angeles, Vis Lab, Los Angeles, CA 90095 USA

来源：

2015 IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR) | 2015年

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

We introduce a simple modification of local image descriptors, such as SIFT, based on pooling gradient orientations across different domain sizes, in addition to spatial locations. The resulting descriptor, which we call DSP-SIFT, outperforms other methods in wide-baseline matching benchmarks, including those based on convolutional neural networks, despite having the same dimension of SIFT and requiring no training.

引用

页码：5097 / 5106

页数：10

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