کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
4968874 1449749 2016 24 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Robust object tracking by online Fisher discrimination boosting feature selection
ترجمه فارسی عنوان
ردیابی دقیق از طریق انتخاب ویژگی های تبعیض آمیز فیشر آنلاین
کلمات کلیدی
ردیابی ویژوال فیلتر ذرات، تقویت، تبعیض فیشر،
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر چشم انداز کامپیوتر و تشخیص الگو
چکیده انگلیسی
Large appearance changes in visual tracking affect the tracking performance severely. To address this challenge, in this paper we develop an effective appearance model with the highly discriminative features. We propose an online Fisher discrimination boosting feature selection mechanism, which selects features that reduce the with-in scatter while enlarging the between-class scatter, thereby enhancing the discriminative capability between the target and background. Moreover, we utilize a particle filtering framework for visual tracking, in which the weights of candidate particles take into account the context information around the particles, thereby enhancing the robustness of tracking. In order to increase efficiency, a coarse-to-fine search strategy is exploited to efficiently and accurately locate the target. Extensive experiments on the CVPR2013 tracking benchmark demonstrate the competitive performance of our algorithm over other representative algorithms in terms of accuracy and robustness.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computer Vision and Image Understanding - Volume 153, December 2016, Pages 100-108
نویسندگان
, , ,