SUMMARYIt is commonly believed that improved interaction between humans and electronic device, it is effective to draw the viewer's attention to a particular object. Augmented reality (AR) applications can call attention to real objects by overlaying highlight effects or visual stimuli (such as arrows) on a physical scene. Sometimes, more subtle effects would be desirable, in which case it would be necessary to smoothly and naturally guide the user's gaze without external stimuli. Here, a novel image modification method is proposed for directing a viewer's gaze to specific regions of interest. The proposed method uses saliency analysis and color modulation to create modified images in which the region of interest is the most salient region in the entire image. The proposed saliency map model that is used during saliency analysis reduces computational costs and improves the naturalness of the image using the LAB color space and simplified normalization. During color modulation, the modulation value of each LAB component is determined in order to consider the relationship between the LAB components and the saliency value. With the image obtained in this manner, the viewer's attention is smoothly attracted to a specific region very naturally. Gaze measurements as well as a subjective experiments were conducted to prove the effectiveness of the proposed method. These results show that a viewer's visual attention is indeed attracted toward the specified region without any sense of discomfort or disruption when the proposed method is used.
SUMMARYThis paper presents a method for gender and age estimation which is robust to changing facial pose. We propose a feature point detection method, called the adapted retinal sampling method (ARSM), and a feature extraction method. A basic concept of the ARSM is to add knowledge about the facial structure to the retinal sampling method. In this method, feature points are detected on the basis of seven points corresponding to facial organs from a facial image. The reason why we used seven points as the basis of feature point detection is that facial organs are conspicuous in the facial region, and are comparatively easy to extract. As features robust to changing facial pose, skin texture, hue, and the Gabor jet are used for gender and age estimation. For classification of gender and estimation of age, we use a multilayered neural network. We also examine the left-right symmetry of faces in connection with gender and age estimation by the proposed method.
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