Background Removal

1
Background Removal

• David Harwin
• Adviser Petros Faloutsos

2
The State of the Art

• This field has been one of great interest in the
  past decade
• There have been many recent papers on the topic
  with intended applications ranging from visual
  effects processing to ...
• In order to determine how to proceed, I have
  spent the quarter reading and analyzing existing
  papers.

3
Identifying motion

• pixel differencing vs optical flow
• differencing vulnerable to signal noise,
  illumination changes, and BG motion
• optical flow is computationally expensive
• most opted for hybrid approach
• only Criminisi (2006) avoids optical flow
  altogether, and instead uses spatio-temporal
  continuity of labels

4
Segmentation

• 2-pass approach
• low-level then high-level (Calderara, Tsai,
  Calic)?
• Calderara - 2nd pass checks for consistency of
  changes in color and intensity over time. Objects
  with insufficiently coherent motion are ignored
  as BG
• Tsai 1st pass initial labelling (constantly vs
  never changing), 2nd only works on uncertain
  pixels
• Calic - creates low-resolution representation,
  corrects BG for camera motion through matrix
  transformations, determines most salient
  frames, then calculation of regions of interest
  occurs only on these keyframes
• high-level then low-level (Park)?
• Park - object tracking, followed by pixel
  differencing inside the object window
• Single pass
• Criminisi -

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Key Features