Robust Photometric Invariant Features from the Color Tensor J. van de Weijer, T. Gevers, A. W. M. Smeulders In IEEE Transactions on Image Processing 2006. [bibtex] [pdf] [url]

Luminance-based features are widely used as low-level input for computer vision applications, even when color data is available. Extension of feature detection to the color domain prevents information loss due to isoluminance and allows to exploit the photometric information. To fully exploit the extra information in the color data, the vector nature of color data has to be taken into account and a sound framework is needed to combine feature and photometric invariance theory. In this paper we focus on the structure tensor, or color tensor, which adequately handles the vector nature of color images. Further, we combine the features based on the color tensor with photometric invariant derivatives to arrive at photometric invariant features. We circumvent the drawback of unstable photometric invariants by deriving an uncertainty measure to accompany the photometric invariant derivatives. The uncertainty is incorporated in the color tensor, hereby allowing the computation of robust photometric invariant features. The combination of the photometric invariance theory and tensorbased features allows for detection of a variety of features such as photometric invariant edges, corners, optical flow and curvature. The proposed features are tested for noise characteristics and robustness to photometric changes. Experiments show that the proposed features are robust to scene incidental events and that the proposed uncertainty measure improves the applicability of full invariants.

@Article{vandeWeijerTIP2006,
  author       = "van de Weijer, J. and Gevers, T. and Smeulders, A. W. M.",
  title        = "Robust Photometric Invariant Features from the Color Tensor",
  journal      = "IEEE Transactions on Image Processing",
  pages        = "118--127",
  year         = "2006",
  url          = "https://ivi.fnwi.uva.nl/isis/publications/2006/vandeWeijerTIP2006",
  pdf          = "https://ivi.fnwi.uva.nl/isis/publications/2006/vandeWeijerTIP2006/vandeWeijerTIP2006.pdf",
  has_image    = 1
}