Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/115495
Title: Fast and accurate global motion compensation
Authors: Déniz Suárez,Oscar 
Bueno, G
Bermejo, E
Sukthankar, R
UNESCO Clasification: 3304 Tecnología de los ordenadores
Keywords: Global motion estimation
Action recognition
Issue Date: 2011
Journal: PATTERN RECOGNITION
Abstract: Video understanding has attracted significant research attention in recent years, motivated by interest in video surveillance, rich media retrieval and vision-based gesture interfaces. Typical methods focus on analyzing both the appearance and motion of objects in video. However, the apparent motion induced by a moving camera can dominate the observed motion, requiring sophisticated methods for compensating for camera motion without a priori knowledge of scene characteristics. This paper introduces two new methods for global motion compensation that are both significantly faster and more accurate than state of the art approaches. The first employs RANSAC to robustly estimate global scene motion even when the scene contains significant object motion. Unlike typical RANSAC-based motion estimation work, we apply RANSAC not to the motion of tracked features but rather to a number of segments of image projections. The key insight of the second method involves reliably classifying salient points into foreground and background, based upon the entropy of a motion inconsistency measure. Extensive experiments on established datasets demonstrate that the second approach is able to remove camera-based observed motion almost completely while still preserving foreground motion. © 2011 Elsevier Ltd. All rights reserved.
URI: http://hdl.handle.net/10553/115495
ISSN: 0031-3203
DOI: 10.1016/j.patcog.2010.10.019
Source: Pattern Recognition, Volume 44, Issue 12,
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