Sparse vs. Non-sparse: Which One Is Better for Practical Visual Tracking?

نویسندگان

  • Yashar Deldjoo
  • Shengping Zhang
  • Bahman Zanj
  • Paolo Cremonesi
  • Matteo Matteucci
چکیده

Recently, sparse representation based visual tracking methods have attracted increasing attention in the computer vision community. Although achieve superior performance to traditional tracking methods, however, a basic problem has not been answered yet — that whether the sparsity constrain is really needed for visual tracking? To answer this question, in this paper, we first propose a robust non-sparse representation based tracker and then conduct extensive experiments to compare it against several state-of-the-art sparse representation based trackers. Our experiment results and analysis indicate that the proposed non-sparse tracker achieved competitive tracking accuracy with sparse trackers while having faster running speed, which support our non-sparse tracker to be used in practical applications.

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عنوان ژورنال:
  • CoRR

دوره abs/1608.00168  شماره 

صفحات  -

تاریخ انتشار 2016