کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
4969629 | 1449975 | 2017 | 10 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Hand action detection from ego-centric depth sequences with error-correcting Hough transform
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
چشم انداز کامپیوتر و تشخیص الگو
پیش نمایش صفحه اول مقاله
چکیده انگلیسی
Detecting hand actions from ego-centric depth sequences is a practically challenging problem, owing mostly to the complex and dexterous nature of hand articulations as well as non-stationary camera motion. We address this problem via a Hough transform based approach coupled with a discriminatively learned error-correcting component to tackle the well known issue of incorrect votes from the Hough transform. In this framework, local parts vote collectively for the start & end positions of each action over time. We also construct an in-house annotated dataset. Our system is empirically evaluated on this real-life dataset as well as a synthetic dataset, where it is shown to deliver favorable results in real-time (around 112 frame-per-second). To facilitate reproduction, the new dataset and our implementation are also provided online.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Pattern Recognition - Volume 72, December 2017, Pages 494-503
Journal: Pattern Recognition - Volume 72, December 2017, Pages 494-503
نویسندگان
Chi Xu, Lakshmi Narasimhan Govindarajan, Li Cheng,