Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Fast Approximate Matching of Cell-Phone Videos for Robust Background
  Subtraction   We identify a novel instance of the background subtraction problem that
focuses on extracting near-field foreground objects captured using handheld
cameras. Given two user-generated videos of a scene, one with and the other
without the foreground object(s), our goal is to efficiently generate an output
video with only the foreground object(s) present in it. We cast this challenge
as a spatio-temporal frame matching problem, and propose an efficient solution
for it that exploits the temporal smoothness of the video sequences. We present
theoretical analyses for the error bounds of our approach, and validate our
findings using a detailed set of simulation experiments. Finally, we present
the results of our approach tested on multiple real videos captured using
handheld cameras, and compare them to several alternate foreground extraction
approaches.

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The categories of this paper are: nlin
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The categories of this paper are: mtrl-th
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The categories of this paper are: hep-ph
28
The categories of this paper are: alg-geom
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The categories of this paper are: ao-sci
30
The categories of this paper are: q-alg
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The categories of this paper are: gr-qc
2
The categories of this paper are: math
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The categories of this paper are: q-fin
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The categories of this paper are: econ
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The categories of this paper are: cond-mat
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The categories of this paper are: stat
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The categories of this paper are: chao-dyn
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The categories of this paper are: nucl-th
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The categories of this paper are: eess
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The categories of this paper are: plasm-ph