کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
10360411 | 869792 | 2014 | 16 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Visual tracking via weakly supervised learning from multiple imperfect oracles
ترجمه فارسی عنوان
ردیابی ویژوال از طریق یادگیری تحت نظارت از چندین ناقص چندگانه
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کلمات کلیدی
ردیابی ویژوال آموزش ضعیف تحت نظارت، تلفیق اطلاعات، یادگیری آنلاین، مدل ظاهری سازگار، مشکل رانش ارزیابی آنلاین،
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
چشم انداز کامپیوتر و تشخیص الگو
چکیده انگلیسی
Notwithstanding many years of progress, visual tracking is still a difficult but important problem. Since most top-performing tracking methods have their strengths and weaknesses and are suited for handling only a certain type of variation, one of the next challenges is to integrate all these methods and address the problem of long-term persistent tracking in ever-changing environments. Towards this goal, we consider visual tracking in a novel weakly supervised learning scenario where (possibly noisy) labels but no ground truth are provided by multiple imperfect oracles (i.e., different trackers). These trackers naturally have intrinsic diversity due to their different design strategies, and we propose a probabilistic method to simultaneously infer the most likely object position by considering the outputs of all trackers, and estimate the accuracy of each tracker. An online evaluation strategy of trackers and a heuristic training data selection scheme are adopted to make the inference more effective and efficient. Consequently, the proposed method can avoid the pitfalls of purely single tracking methods and get reliably labeled samples to incrementally update each tracker (if it is an appearance-adaptive tracker) to capture the appearance changes. Extensive experiments on challenging video sequences demonstrate the robustness and effectiveness of the proposed method.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Pattern Recognition - Volume 47, Issue 3, March 2014, Pages 1395-1410
Journal: Pattern Recognition - Volume 47, Issue 3, March 2014, Pages 1395-1410
نویسندگان
Bineng Zhong, Hongxun Yao, Sheng Chen, Rongrong Ji, Tat-Jun Chin, Hanzi Wang,