In this study, we investigate whether a telepresence robot enhances the persuasiveness of a remote boss, which is measured by the behavior changes or opinion changes of the communication partner. In our study, we used the telepresence robot as a proxy of the teleworking boss. We designed a simplified in-basket test to enable quantitative measurement of the task outcome. We also included a questionnaire as a subjective measure. In our experiment, we tested whether the movements of the robot affect the persuasiveness of the remote boss. The task outcome showed that the robot's movements had no effect in terms of persuasiveness. Interestingly, however, the questionnaire results suggest that the movements of the robot, especially its orientation toward individual subordinates when giving comments, seemed to strengthen the sense of pressure subordinates experienced when performing a task.

The mood of an image is typically conveyed by the combination of colors. Such a combination of colors is called a color theme. In this paper, we propose a color transformation method based on color theme that can i) control the ratios of assigned colors while ii) maintaining the spatial coherence of regions. In our color transformation method, one color in a color theme is assigned to the pixels in an image and the pixels are transformed toward the corresponding color. We consider the color assignment problem as a labeling problem. To ensure that i) and ii) above can be achieved, we introduce offsets that are added to labeling costs in the label optimization process. The offsets are determined according to the concept of maximally stable extremal regions (MSER) in order to preserve spatial coherence. Experimental results show that our approach is effective for the control of the color ratios and preserving the coherence of the regions.

An affective style of human motion is essential for human computer interaction using embodied conversational agents. Motion synthesis for affective agents generates a skeletal motion in a particular affective style (briefly called affective motion in this paper) from an input neutral motion. This appeals to the user but is very challenging due to the well-known fact that a skeletal motion is a high-dimensional and non-linear signal. We solve this problem by using regression analysis to estimate the relationship between neutral motions and affective motions, adopting principal component regression (PCR) to deal with the high-dimensional motion signal for the first time. Furthermore, we propose a novel method called piecewise principal component regression (PPCR) to deal with the non-linear problem, in which the motion signal is automatically divided into several segments and PCR is performed on each segment. Our experimental results demonstrate that the proposed PPCR method is successful in generating affective motion within high quality.

In this paper, we present a practical and automatic comic-like image layout system for event photos or event movies. We focus on the comic-like layout with cropping. The comic-like layouts allow viewers to track events in time sequential order like comic books, in which event images are cropped and arranged in panels from top left to bottom right on a screen so that the resultant layout has variety of image shapes and gives a pleasant impression. The main drawback of the conventional method is that an important region such as a face or a salient object area is sometimes cropped. In order to avoid excessive cropping of important regions while maintaining the image order, our system achieves adaptive layout to input images by generating all possible templates suitable for comic and deciding appropriate templates based on our proposed layout evaluation. In the demo, we will show that our full automatic system generates comic-like layouts immediately. Furthermore, the system allows a user to select his/her favorite layout from the multiple ones with different looks.

This paper proposes a novel visual cryptography method that embeds a natural secret image into two natural carrier images with high quality at low computational complexity. The secret image is decoded visually by superposing the two carrier images. For some applications such as entertainment use, all three images should be high quality natural images and low computational complexity is also required. However, in the conventional methods, picture quality and processing speed have been tradeoff relations. To solve this problem, we propose a method which is based on conventional visual cryptography using error diffusion halftoning and introduce an additional feedback mechanism to embed the high quality natural image. Experimental results show that the proposed method can achieve higher quality natural images of a superposed image and carrier images while computational complexity is maintained low when compared with the conventional methods.

In this paper, visual cryptography for halftone images is proposed, which uses threshold arrays generated by a void-and-cluster method. The proposed halftone visual cryptography (HFC) using threshold arrays shows great flexibility for a combination of share images in order to decode a secret image. Moreover, it also achieves high quality share images, high speed processing and extensibility to (k,n) the visual cryptography of three share image categories, such as (2,3) or (3,3). Simulation results show that all the above features are achieved, while a secret image is clearly decoded, and the secret image cannot be seen on each share image.