کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6876540 | 690949 | 2015 | 11 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Progressive 3D shape segmentation using online learning
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موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
گرافیک کامپیوتری و طراحی به کمک کامپیوتر
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چکیده انگلیسی
Our framework uses Online Multi-Class LPBoost (OMCLP) to train/update a segmentation model progressively, which includes several Online Random forests (ORFs) as the weak learners. Then, it performs graph cuts optimization to segment the 3D shape by using the trained/updated segmentation model as the optimal data term. There exist three features of our framework. Firstly, the segmentation model can be trained gradually during the collection of the shapes. Secondly, the segmentation results can be refined progressively until users' requirements are met. Thirdly, the segmentation model can be updated incrementally without retraining all shapes when users add new shapes. Experimental results demonstrate the effectiveness of our approach.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computer-Aided Design - Volume 58, January 2015, Pages 2-12
Journal: Computer-Aided Design - Volume 58, January 2015, Pages 2-12
نویسندگان
Feiqian Zhang, Zhengxing Sun, Mofei Song, Xufeng Lang,