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The remainders are calculated using the background subtraction and object segmentation schemes described in [14].
The most popular methods are based in background subtraction and object detection.
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Among the 10 papers dealing with early processing stages in video surveillance, two are in the area of tracking, five devoted to background subtraction, and three relate to object detection.
Cucchiara et al. [20] proposed an approach which exploits color information for both background subtraction and shadow detection to improve object segmentation and background update.
As shown in Figure 1, automatic location of the head is achieved by segmenting the target using background subtraction and morphological operations with a kernel biased towards the scale of the target to identify objects.
Given the deduced background subtraction and post-filtering parameters, the performance of the object detection subsystems is not measured.
This article presents a new method for background subtraction (BGS) and object detection for a real-time video application using a combination of frame differencing and a scale-invariant feature detector.
The second column shows background subtraction: d the image used as the background model, e the frame of interest prior to background subtraction, and f the foreground image.
Image processing, background subtraction, and the construction of an unbiased ratio image are discussed.
The signal values were derived by background subtraction and normalization.
Background subtraction and Gaussian filtering was performed before signal identification.
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