Motion Segmentation and Depth Ordering Using an Occlusion Detector
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资源说明:Abstract— We present a novel method for motion segmentation
and depth ordering from a video sequence in general motion.
We first compute motion segmentation based on differential
properties of the spatio-temporal domain, and scale-space inte-
gration. Given a motion boundary, we describe two algorithms to
determine depth ordering from two- and three-frame sequences.
A remarkable characteristic of our method is its ability compute
depth ordering from only two frames. The segmentation and
depth ordering algorithms are shown to give good results on 6
real sequences taken in general motion. We use synthetic data to
show robustness to high levels of noise and illumination changes;
we also include cases where no intensity edge exists at the
location of the motion boundary, or when no parametric motion
model can describe the data. Finally, we describe psychophysical
experiments showing that people, like our algorithm, can compute
depth ordering from only two frames, even when the boundary
between the layers is not visible in a single frame.
Index Terms— Computer vision, Video analysis, Motion, Depth
cues, Segmentation
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