Fast Edge-Preserving PatchMatch for Large Displacement Optical Flow

被引：58

作者：

Bao, Linchao ^{[1
]}

Yang, Qingxiong ^{[1
]}

Jin, Hailin ^{[2
]}

机构：

[1] City Univ Hong Kong, Hong Kong, Hong Kong, Peoples R China

[2] Adobe Res, Dartmouth, NS, Canada

来源：

2014 IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR) | 2014年

关键词：

D O I：

10.1109/CVPR.2014.452

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

We present a fast optical flow algorithm that can handle large displacement motions. Our algorithm is inspired by recent successes of local methods in visual correspondence searching as well as approximate nearest neighbor field algorithms. The main novelty is a fast randomized edge-preserving approximate nearest neighbor field algorithm which propagates self-similarity patterns in addition to offsets. Experimental results on public optical flow benchmarks show that our method is significantly faster than state-of-the-art methods without compromising on quality, especially when scenes contain large motions.

引用

页码：3534 / 3541

页数：8