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The Kinect sensor released by Microsoft is well-known for its effectiveness on human gesture recognition. Gesture recognition by Kinect has been proved to be an efficient command operation and provides an additional human-computer interface in addition to the traditional speech recognition. For Kinect gesture recognition in the application of gesture command operations, recognition of the active user making the gesture command to Kinect will be an extremely crucial problem. The purpose of this paper is to propose a recognition method for recognizing the person identity of an active user using combined eigenspace and Gaussian mixture model (GMM) with Kinect-extracted action gesture features.

Several Kinect-derived gesture features will be explored for determining the effective pattern features in the active user recognition task. In this work, a separate Kinect-derived feature design for eigenspace recognition and GMM classification is presented for achieving the optimal performance of each individual classifier. In addition to Kinect-extracted feature designs for active user recognition, this study will further develop a combined recognition method, called combined eigenspace-GMM, which properly hybridizes the decision information of both the eigenspace and the GMM for making a more reliable user recognition result.

Active user recognition using an effective combination of eigenspace and GMM with well-developed active gesture features in Kinect-based active user recognition will have an outstanding performance on the recognition accuracy. The presented Kinect-based user recognition system using the presented approach will further have the competitive benefits of recognition on both gesture commands and providing users of gesture commands.

A hybridized scheme of eigenspace and GMM performs better than eigenspace-alone or GMM-alone on recognition accuracy of active user recognition; a separate Kinect-derived feature design for eigenspace recognition and GMM classification is presented for achieving the optimal performance of the individual classifier; combined eigenspace-GMM active user recognition belonging to model-based active user recognition design has a fine extension on increasing the recognition rate by adjusting recognition models.

Drawing on virtual liminoid theory, the purpose of this paper is to examine factors that induce a multisensory flow experience in an e-shopping context through the use of augmented-reality interactive technology (ARIT).

To validate the research framework, a task-based laboratory study was performed. Participants were recruited through a snowball e-mail method and requested to freely and independently use ARIT for clothes fitting in the laboratory, after which they completed a questionnaire; 336 valid responses were received.

Empirical results revealed that three decorating psychological states (sense of body ownership, sense of ownership control, and self-explorative engagement) directly induced a multisensory flow experience. Furthermore, two multisensory factors (sense of self-location and haptic imagery) mediated the multisensory flow experience through these three decorating psychological states.

Consumers not only rely on generating self-display for optimal fitting in virtual avatar decoration in an e-shopping context but also concentrate more on expression and control of self-body. As consumers’ decorating psychological states require an ideal form of self-expression, a high degree of autonomy in exploring self-decoration options will create more value for consumers. Considering that expressing and controlling the self-body in addition to self-explorative engagement in virtual avatar decoration will trigger the flow experience in an e-shopping context, increasing the use of multisensory ARIT to trigger decorating psychological states in e-shopping contexts is highly recommended.

In this study, a relationship was constructed among virtual liminoid theory, flow theory, and multisensory technology, and an integrated conceptual framework was developed for the relationship between decorating psychological states and multisensory flow experience.