Expression transmission using exaggerated animation for Elfoid

We propose an expression transmission system using a cellular-phone-type teleoperated robot called Elfoid. Elfoid has a soft exterior that provides the look and feel of human skin, and is designed to transmit the speaker's presence to their communication partner using a camera and microphone.To transmit the speaker's presence, Elfoid sends not only the voice of the speaker but also the facial expression captured by the camera. In this research, facial expressions are recognized using a machine learning technique. Elfoid cannot, however, display facial expressions because of its compactness and a lack of sufficiently small actuator motors. To overcome this problem, facial expressions are displayed using Elfoid's head-mounted mobile projector. In an experiment, we built a prototype system and experimentally evaluated its subjective usability

Extracting discriminative features using task-oriented gaze maps measured from observers for personal attribute classification

We discuss how to reveal and use the gaze locations of observers who view pedestrian images for personal attribute classification. Observers look at informative regions when attempting to classify the attributes of pedestrians in images. Thus, we hypothesize that the regions in which observers’ gaze locations are clustered will contain discriminative features for the classifiers of personal attributes. Our method acquires the distribution of gaze locations from several observers while they perform the task of manually classifying each personal attribute. We term this distribution a task-oriented gaze map. To extract discriminative features, we assign large weights to the region with a cluster of gaze locations in the task-oriented gaze map. In our experiments, observers mainly looked at different regions of body parts when classifying each personal attribute. Furthermore, our experiments show that the gaze-based feature extraction method significantly improved the performance of personal attribute classification when combined with a convolutional neural network or metric learning technique

Temperature-dependent Color Change of Cholesteric Liquid Crystalline Core-shell Microspheres

We have fabricated water-in-oil-in-water (W/O/W) double emulsion droplets with a cholesteric liquid crystalline (CLC) material, which is a mixture of a nematic liquid crystalline compound, 4-cyano-4′-pentylbiphenyl (5CB), and a chiral dopant, cholesteryl oleyl carbonate (COC), as the middle phase and an aqueous poly(vinylalcohol) (PVA) solution as the inner and outer phases (CLC core-shell microspheres). Here we report the strongly temperature-dependent color change of CLC core-shell microsphere.This is an Accepted Manuscript of an article published by Taylor & Francis in Molecular Crystals and Liquid Crystals on 3 July 2015, available at https://doi.org/10.1080/15421406.2015.1066548

Effect of Laughter Yoga on Pulmonary Rehabilitation in Patients with Chronic Obstructive Pulmonary Disease.

Objective: To evaluate the clinical usefulness of laughter yoga for patients with chronic obstructive pulmonary disease (COPD) in a pulmonary rehabilitation setting. Design: Pilot study, with randomization of participants. Setting: This study was conducted by the Yoshino-cho National Health Insurance Yoshino Hospital Department of Internal Medicine. Participants: Stable outpatients with COPD (7 men and 1 woman, age 64 to 84 years) participated in the pulmonary rehabilitation program during a 2-week period. Intervention : The patients were divided into two groups based on a sealed envelope randomization method. The laughter yoga group had a 10-min laughter yoga session before exercise training. Patients in both groups had exercise training, educational programs, lung physiotherapy, and nutrition counseling. Outcome Measures: Health-related quality of life using the St. George's Respiratory Questionnaire (SGRQ) and the Medical Research Council (MRC) Health Survey Short Form 36-item (SF-36), depression scores using the Self-rating Depression Scale (SDS), anxiety scores using State-Trait Anxiety Inventory (STAI), and spirometry, the 6-minute walk test and mMRC dyspnea scale results were evaluated before and at 2 weeks after the program in both groups. Results: There were significant improvements in the SGRQ impacts domain and the SF-36 general health domain in the laughter yoga group, while the SF-36 physical functioning domain significantly improved in the control group. SDS and STAI result did not significantly change in either group. Spirometry, the 6-minute walk test, and MRC dyspnea scale results did not significantly change in either group. Conclusion: Laughter yoga may improve the psychological quality of life in patients with COPD