Augmented lazy snapping: how does pre-segmentation help lazy snapping framework?

2018 ◽  
Author(s):  
Nam Tran Hoang ◽  
Dong sun Seo ◽  
Trung Hieu Tu
Keyword(s):  
Lazy Snapping

Lazy snapping

2004 ◽  
Author(s):  
Yin Li ◽  
Jian Sun ◽  
Chi-Keung Tang ◽  
Heung-Yeung Shum
Keyword(s):  
Lazy Snapping

scholarly journals Guided lazy snapping for long thin object selection

2018 ◽  
Vol 189 ◽  
pp. 10026
Author(s):  
Nam H. Tran ◽  
Dongsun Seo ◽  
Henry T.H. Tu
Keyword(s):  
Image Segmentation ◽  
Connected Components ◽  
Segmentation Method ◽  
User Interactions ◽  
Object Selection ◽  
Segmentation Methods ◽  
Background Image ◽  
Lazy Snapping

We show a novel way to select long thin objects in an image by enhancing the output of the existing foreground/background image segmentation methods. Most superpixel-based methods fail to select the long thin details, such as legs and whiskers, and extended curves from the main objects. We observe, however, the output without long thin details, can be used as the guided information to obtain the connected components. Based on this observation, our Guided Lazy Snapping method overcomes the limitation of the Lazy Snapping methods (or other alternatives superpixel-based segmentation method) to select long thin objects. The results show that connected components in the image can be selected without having a lot of user interactions (mouse clicks) on each extended parts of the object.

Lazy snapping

2004 ◽  
Vol 23 (3) ◽  
pp. 303-308 ◽  
Author(s):  
Yin Li ◽  
Jian Sun ◽  
Chi-Keung Tang ◽  
Heung-Yeung Shum
Keyword(s):  
Lazy Snapping
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