@inproceedings{8826835d382849cb99413eda92b2ef7f,
title = "A combined local-global match for optical flow",
abstract = "Optical flow estimation is still an open question in computer vision. Matching is the initialization of the final optical flow results. A good matching is important for the flow. In this paper, a combined local-global matching method is proposed. The local matching method and the global method are integrated together to make a trade-off between the large displacement and local consistency of optical flow. Extensive experiments on state-of-art challenging datasets MPI-Sintel show that the proposed method is efficient and effective.",
keywords = "Global, Matching method, Non-local, Optical flow",
author = "Yueran Zu and Wenzhong Tang and Xiuguo Bao and Ke Gao and Mingdong Zhang",
note = "Publisher Copyright: {\textcopyright} Springer Nature Singapore Pte Ltd., 2018.; 13th Conference on Image and Graphics Technologies and Applications, IGTA 2018 ; Conference date: 08-04-2018 Through 10-04-2018",
year = "2018",
doi = "10.1007/978-981-13-1702-6\_19",
language = "英语",
isbn = "9789811317019",
series = "Communications in Computer and Information Science",
publisher = "Springer Verlag",
pages = "192--200",
editor = "Yongtian Wang and Yuxin Peng and Zhiguo Jiang",
booktitle = "Image and Graphics Technologies and Applications - 13th Conference on Image and Graphics Technologies and Applications, IGTA 2018, Revised Selected Papers",
address = "德国",
}