Literature DB >> 22156095

Motion detail preserving optical flow estimation.

Li Xu1, Jiaya Jia, Yasuyuki Matsushita.   

Abstract

A common problem of optical flow estimation in the multiscale variational framework is that fine motion structures cannot always be correctly estimated, especially for regions with significant and abrupt displacement variation. A novel extended coarse-to-fine (EC2F) refinement framework is introduced in this paper to address this issue, which reduces the reliance of flow estimates on their initial values propagated from the coarse level and enables recovering many motion details in each scale. The contribution of this paper also includes adaptation of the objective function to handle outliers and development of a new optimization procedure. The effectiveness of our algorithm is demonstrated by Middlebury optical flow benchmarkmarking and by experiments on challenging examples that involve large-displacement motion.

Year:  2012        PMID: 22156095     DOI: 10.1109/TPAMI.2011.236

Source DB:  PubMed          Journal:  IEEE Trans Pattern Anal Mach Intell        ISSN: 0098-5589            Impact factor:   6.226


  3 in total

1.  PORTR: Pre-operative and post-recurrence brain tumor registration.

Authors:  Dongjin Kwon; Marc Niethammer; Hamed Akbari; Michel Bilello; Christos Davatzikos; Kilian M Pohl
Journal:  IEEE Trans Med Imaging       Date:  2014-03       Impact factor: 10.048

2.  Line-Constrained Camera Location Estimation in Multi-Image Stereomatching.

Authors:  Simon Donné; Bart Goossens; Wilfried Philips
Journal:  Sensors (Basel)       Date:  2017-08-23       Impact factor: 3.576

3.  Motion field estimation for a dynamic scene using a 3D LiDAR.

Authors:  Qingquan Li; Liang Zhang; Qingzhou Mao; Qin Zou; Pin Zhang; Shaojun Feng; Washington Ochieng
Journal:  Sensors (Basel)       Date:  2014-09-09       Impact factor: 3.576

  3 in total

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