کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
4968697 | 1449740 | 2017 | 16 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
mdBRIEF - a fast online-adaptable, distorted binary descriptor for real-time applications using calibrated wide-angle or fisheye cameras
دانلود مقاله + سفارش ترجمه
دانلود مقاله ISI انگلیسی
رایگان برای ایرانیان
کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
چشم انداز کامپیوتر و تشخیص الگو
پیش نمایش صفحه اول مقاله
چکیده انگلیسی
Fast binary descriptors build the core for many vision based applications with real-time demands like object detection, visual odometry or SLAM. Commonly it is assumed, that the acquired images and thus the patches extracted around keypoints originate from a perspective projection ignoring image distortion or completely different types of projections such as omnidirectional or fisheye. Usually the deviations from a perfect perspective projection are corrected by using standard undistortion models. The latter, however, introduce artifacts if the camera's field-of-view gets larger. In addition, many applications (e.g. monocular SLAM) require only undistorted points and holistic undistortion of every image for descriptor extraction could be eluded. In this paper, we propose a distorted and masked version of the BRIEF descriptor for calibrated cameras, called dBRIEF and mdBRIEF respectively. Instead of correcting the distortion holistically, we distort the binary tests and thus adapt the descriptor to different image regions. The implementation of the proposed method along with evaluation scripts can be found online at https://github.com/urbste/mdBRIEF.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computer Vision and Image Understanding - Volume 162, September 2017, Pages 71-86
Journal: Computer Vision and Image Understanding - Volume 162, September 2017, Pages 71-86
نویسندگان
Steffen Urban, Martin Weinmann, Stefan Hinz,