17 April 2006 Position, rotation, scale, and orientation invariant object tracking from cluttered scenes
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A method of tracking objects in video sequences despite any kind of perspective distortion is demonstrated. Moving objects are initially segmented from the scene using a background subtraction method to minimize the search area of the filter. A variation on the Maximum Average Correlation Height (MACH) filter is used to create invariance to orientation while giving high tolerance to background clutter and noise. A log r-θ mapping is employed to give invariance to in-plane rotation and scale by transforming rotation and scale variations of the target object into vertical and horizontal shifts. The MACH filter is trained on the log r-θ map of the target for a range of orientations and applied sequentially over the regions of movement in successive video frames. Areas of movement producing a strong correlation response indicate an in-class target and can then be used to determine the position, in-plane rotation and scale of the target objects in the scene and track it over successive frames.
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Peter Bone, Rupert Young, Chris Chatwin, "Position, rotation, scale, and orientation invariant object tracking from cluttered scenes", Proc. SPIE 6245, Optical Pattern Recognition XVII, 624508 (17 April 2006); doi: 10.1117/12.664048; https://doi.org/10.1117/12.664048

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