menpofit.math.mccf(X, y, l=0.01, boundary='constant', crop_filter=True)[source]

Multi-Channel Correlation Filter (MCCF).

  • X ((n_images, n_channels, image_h, image_w) ndarray) – The training images.

  • y ((1, response_h, response_w) ndarray) – The desired response.

  • l (float, optional) – Regularization parameter.

  • boundary ({'constant', 'symmetric'}, optional) – Determines how the image is padded.

  • crop_filter (bool, optional) – If True, the shape of the MOSSE filter is the same as the shape of the desired response. If False, the filter’s shape is equal to: X[0].shape + y.shape - 1


  • f ((1, response_h, response_w) ndarray) – Multi-Channel Correlation Filter (MCCF) filter associated to the training images.

  • sXY ((N,) ndarray) – The auto-correlation array, where N = (image_h+response_h-1) * (image_w+response_w-1) * n_channels.

  • sXX ((N, N) ndarray) – The cross-correlation array, where N = (image_h+response_h-1) * (image_w+response_w-1) * n_channels.



H. K. Galoogahi, T. Sim, and Simon Lucey. “Multi-Channel Correlation Filters”. IEEE Proceedings of International Conference on Computer Vision (ICCV), 2013.