کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
10361278 | 870090 | 2015 | 46 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Hybrid support vector machines for robust object tracking
ترجمه فارسی عنوان
ماشین های بردار پشتیبانی ترکیبی برای ردیابی شیء قوی
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
چشم انداز کامپیوتر و تشخیص الگو
چکیده انگلیسی
Tracking-by-detection techniques always formulate tracking as a binary classification problem. However, in this formulation, there exists a potential issue that the boundary of the positive targets and the negative background samples is fuzzy, which may be an important factor causing drift. To address this problem, we propose a novel hybrid formulation for tracking based on binary classification, regression and one-class classification, which comprehensively represents the appearance from different perspectives. In particular, the proposed regression model is a novel formulation for tracking and plays an important role in solving the fuzzy boundary problem. Moreover, we present a new tracking approach with different support vector machines (SVMs) and a novel distribution-based collaboration strategy as a specific implementation. Experimental results demonstrate that our method is robust and can achieve the state-of-the-art performance.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Pattern Recognition - Volume 48, Issue 8, August 2015, Pages 2474-2488
Journal: Pattern Recognition - Volume 48, Issue 8, August 2015, Pages 2474-2488
نویسندگان
Shunli Zhang, Yao Sui, Xin Yu, Sicong Zhao, Li Zhang,