Background Subtraction Using Ensembles of Classifiers with an ...

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DEDICATIONMy thesis is dedicated to Fred Klare, Christina Hindman, and the 75th Ranger Regiment.These have been the largest influences and offered the most support in my life. Without them Iwould not be where I am today.RLTW!
Page 1: Background Subtraction Using Ensemb
Page 7 and 8: Figure 5.17 Frame by frame false po
Page 10 and 11: classification because a pixel eith
Page 12 and 13: Difficulties with varying illuminat
Page 14 and 15: comprehensive results using ROC gra
Page 16 and 17: Updating the background image via E
Page 18 and 19: epresentations, and various color s
Page 20: each frame is processed a pixel’s
Page 23 and 24: outliers which comprises the foregr
Page 25: the shortest Euclidean distance fro
Page 30 and 31: Figure 3.1. Set of Haar features be
Page 32: (a) Original Image, no shadow(b) Or
Page 35 and 36: of distributions observed exceeds K
Page 37 and 38: In both [40] and [41], the average
Page 39 and 40: from Classifier A will certainly no
Page 41 and 42: Figure 5.2. Sample frames from PETS
Page 43 and 44: (a) Original Image(b) Non-Threshold
Page 45 and 46: In Figure 5.6, an ROC graph of the
Page 47 and 48: 0.25All FeaturesRGBFrame-by-Frame P
Page 49 and 50: 2001 data set. The same dramatic im
Page 51 and 52: 0.06All FeaturesRGBFrame-by-Frame P
Page 53 and 54:
(a) Original Image(b) All Features,
Page 55 and 56:
PETS 2006 - Total Performance for I
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(a) Original Image(b) Haar 1 Classi
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1OTCBVS - Total Performance0.90.80.
Page 61 and 62:
Figure 6.1. False positive results
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efficient classifier when being res
Page 65 and 66:
REFERENCES[1] R. Jain, R. Kasturi,
Page 67 and 68:
[32] O. Javed, K. Shafique, and M.
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