2008
DOI: 10.1016/j.patrec.2007.09.009
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Parametric active contours for object tracking based on matching degree image of object contour points

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Cited by 16 publications
(17 citation statements)
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“…The continuity is taken as the deformation of temporal sequential images on an identical slice, so the serial slices of digital human can be segmented with the geometric active contour tracking method. A parametric active contour model [16], proposed for object tracking, was applied to brain stem segmentation of Chinese visible human datasets. Since the parametric active contour model tackles the segmentation problem by considering an object boundary as a single and connected structure, the previous model cannot segment several objects simultaneously or the objects with topological changes.…”
Section: Introductionmentioning
confidence: 99%
See 3 more Smart Citations
“…The continuity is taken as the deformation of temporal sequential images on an identical slice, so the serial slices of digital human can be segmented with the geometric active contour tracking method. A parametric active contour model [16], proposed for object tracking, was applied to brain stem segmentation of Chinese visible human datasets. Since the parametric active contour model tackles the segmentation problem by considering an object boundary as a single and connected structure, the previous model cannot segment several objects simultaneously or the objects with topological changes.…”
Section: Introductionmentioning
confidence: 99%
“…To overcome the deficiencies of the model [16], we propose an adaptive geometric active contour model for the segmentation of digital human data in this paper. The construction of the feature image is improved by incorporating the region statistical information into the matching degree image.…”
Section: Introductionmentioning
confidence: 99%
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“…For many applications, computational burden is a critical aspect. This exigency favours selection of fast methods like the parametric snakes [5,19]. This aspect is even more valuable for multi-object segmentation [9].…”
mentioning
confidence: 99%