Incorporating Audio Signals into Constructing a Visual Saliency Map

The saliency map has been proposed to identify regions that draw human visual attention. Differences of features from the surroundings are hierarchially computed for an image or an image sequence in multiple resolutions and they are fused in a fully bottom-up manner to obtain a saliency map. A video usually contains sounds, and not only visual stimuli but also auditory stimuli attract human attention. Nevertheless, most conventional methods discard auditory information and image information alone is used in computing a saliency map. This paper presents a method for constructing a visual saliency map by integrating image features with auditory features. We assume a single moving sound source in a video and introduce a sound source feature. Our method detects the sound source feature using the correlation between audio signals and sound source motion, and computes its importance in each frame in a video using an auditory saliency map. The importance is used to fuse the sound source feature with image features to construct a visual saliency map. Experiments using subjects demonstrate that a saliency map by our proposed method reflects human’s visual attention more accurately than that by a conventional method.