2012 5th International Congress on Image and Signal Processing 2012
DOI: 10.1109/cisp.2012.6469977
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A method of registration based on skeleton for 2-D shapes

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Cited by 3 publications
(3 citation statements)
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“…Since they are heavily influenced by starting point (initial pose) regression techniques are often fooled into local minima and, to compensate, researchers proposed various hierarchical techniques that parametrized depth, changes in resolution, and the number of iterations [7], [11], [12], [16]. Common population based parameters include computational budget, thresholds, and population size.…”
Section: B Challengesmentioning
confidence: 99%
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“…Since they are heavily influenced by starting point (initial pose) regression techniques are often fooled into local minima and, to compensate, researchers proposed various hierarchical techniques that parametrized depth, changes in resolution, and the number of iterations [7], [11], [12], [16]. Common population based parameters include computational budget, thresholds, and population size.…”
Section: B Challengesmentioning
confidence: 99%
“…Factors affecting input include variations in data production or acquisition [13], distortions [18], blurring [18], occlusion [19], and variations in quantity such as extraneous data or noise [12], [20], missing data [14], outliers [20], or variations in the density or distribution of data [9]. These input related issues will hereinafter be referred to as noise and are addressed through greater levels of data abstraction as will be discussed later.…”
Section: B Challengesmentioning
confidence: 99%
“…To speed up the point set matching process, we use the center line to in itialize the init ial value of ICP, and the points on the contour are adopted to iterate again. The center line is the main axis between the upper part contour and the lower part contour by the similar way of the SKICP [14]. The center line is shown in Fig.…”
Section: B Contour Registrationmentioning
confidence: 99%