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QUESTIONING HU'S INVARIANTS: Bad or Good Enough?

机译:质疑胡的不变性:糟糕或足够好吗?

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Despite Hu's invariants were proven not to be independent nor complete long time ago, their use in computer vision applications is still broad, mainly because of their diffusion among common CV libraries and ease of use by inexperienced users. In this paper I want to investigate whether, given their mathematical flaws, they are nevertheless good enough to justify such a wide diffusion, also considering that more sophisticated tools have been developed over the years. In order to do this, I am going to test the robustness of Hu's invariants in a comparative way against the more modern wavelet invariants, in a hand gesture recognition application. Finally, I am going to discuss, basing my considerations on the experimental data, whether Hu's invariants are still a viable option for small scale, amateurish applications, or if the time has come to abandon them for more effective solutions.
机译:尽管HU的不变性被证明不是很长一段时间,但它们在计算机视觉应用中的使用仍然是广泛的,主要是因为它们在普通的CV库之间的扩散和易于经验的用户的易用性。在本文中,我想调查鉴于他们的数学缺陷是否足够好,以证明这种广泛的扩散是合理的,也考虑到多年来已经开发了更复杂的工具。为此,我将以手势识别应用中的比较方式测试胡不变性的鲁棒性,以对更现代的小波不变的方式。最后,我将讨论,基于我对实验数据的考虑,HU的不变性仍然是小规模,业余应用程序的可行选择,或者如果时间来放弃它们以获得更有效的解决方案。

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