Abstract

Visual saliency has been shown to depend on the unpredictability of the visual stimulus given its surround. Various previous works have advocated the equivalence between stimulus saliency and uncompressibility. We propose a direct measure of this quantity, namely the number of bits required by an optimal video compressor to encode a given video patch, and show that features derived from this measure are highly predictive of eye fifixations. To account for global saliency effects, these are embedded in a Markov random fifield model. The resulting saliency measure is shown to achieve state-of-the-art accuracy for the prediction of fifixations, at a very low computational cost. Since most modern cameras incorporate video encoders, this paves the way for in-camera saliency estimation, which could be useful in a variety of computer vision applications.