首页> 外文期刊>The Royal Society Proceedings B: Biological Sciences >Independent component analysis of natural image sequences yields spatio-temporal filters similar to simple cells in primary visual cortex.
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Independent component analysis of natural image sequences yields spatio-temporal filters similar to simple cells in primary visual cortex.

机译:自然图像序列的独立成分分析产生时空滤波器,类似于初级视觉皮层中的简单细胞。

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Simple cells in the primary visual cortex process incoming visual information with receptive fields localized in space and time, bandpass in spatial and temporal frequency, tuned in orientation, and commonly selective for the direction of movement. It is shown that performing independent component analysis (ICA) on video sequences of natural scenes produces results with qualitatively similar spatio-temporal properties. Whereas the independent components of video resemble moving edges or bars, the independent component filters, i.e. the analogues of receptive fields, resemble moving sinusoids windowed by steady Gaussian envelopes. Contrary to earlier ICA results on static images, which gave only filters at the finest possible spatial scale, the spatio-temporal analysis yields filters at a range of spatial and temporal scales. Filters centred at low spatial frequencies are generally tuned to faster movement than those at high spatial frequencies.
机译:初级视觉皮层中的简单细胞处理传入的视觉信息,这些视觉信息具有时域局部性的接受场,时空频率的带通,方向调整以及通常对运动方向具有选择性。结果表明,对自然场景的视频序列执行独立成分分析(ICA)会产生具有在质量上类似的时空特性的结果。视频的独立分量类似于移动边缘或条,而独立分量滤波器(即接收场的类似物)类似于由稳定的高斯包络开窗的移动正弦曲线。与早期在静态图像上的ICA结果相反,后者仅在可能的最佳空间尺度上提供过滤器,时空分析在一系列空间和时间尺度上产生过滤器。通常将以低空间频率为中心的滤波器调整为比高空间频率处的滤波器更快的运动。

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