کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
4970118 | 1450023 | 2017 | 15 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Modeling depth for nonparametric foreground segmentation using RGBD devices
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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
![عکس صفحه اول مقاله: Modeling depth for nonparametric foreground segmentation using RGBD devices Modeling depth for nonparametric foreground segmentation using RGBD devices](/preview/png/4970118.png)
چکیده انگلیسی
The problem of detecting changes in a scene and segmenting the foreground from background is still challenging, despite previous work. Moreover, new RGBD capturing devices include depth cues, which could be incorporated to improve foreground segmentation. In this work, we present a new nonparametric approach where a unified model mixes the device multiple information cues. In order to unify all the device channel cues, a new probabilistic depth data model is also proposed where we show how to handle the inaccurate data to improve foreground segmentation. A new RGBD video dataset is presented in order to introduce a new standard for comparison purposes of this kind of algorithms. Results show that the proposed approach can handle several practical situations and obtain good results in all cases.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Pattern Recognition Letters - Volume 96, 1 September 2017, Pages 76-85
Journal: Pattern Recognition Letters - Volume 96, 1 September 2017, Pages 76-85
نویسندگان
Gabriel Moyà -Alcover, Ahmed Elgammal, Antoni Jaume-i-Capó, Javier Varona,