Author
Abstract
The aim of an object tracker is to generate the trajectory of an object over time
by locating its position in every frame of the video. In this research, we present an
object contour tracking approach using Generalized Gradient Vector Flow
(GGVF). GGVF active contour, or snake, is a dynamic curve that moves within an
image domain to capture desired image features. Mostly, GGVF is not sensitive to
initial conditions and converges to the optimal contour. Given an initial contour
near the object in the first video frame, GGVF can iteratively converge to an
optimal object boundary. In each video frame thereafter, the resulting contour in
the previous video frame is taken as initialization so the algorithm consists of two
steps. In the first step, the initial contour is applied to the desired object in first
video frame. The resulting contour is taken as initialization of the second step,
which applies GGVF to current video frame. To evaluate the tracking performance,
we applied the algorithm to several real world video sequences. Experimental
results are provided.
Keywords
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