Recent advances in virtual reality (VR) technologies such as immersive head-mounted display (HMD), sensing devices, and 3D printing-based props have become much more feasible for providing improved experiences for users in virtual environments. In particular, research on haptic feedback is being actively conducted to enhance the effect of controlling virtual objects. Studies have begun to use real objects that resemble virtual objects, i.e., passive haptic, instead of using haptic equipment with motor control, as an effective method that allows natural interaction. However, technical difficulties must be resolved to match transformations (e.g., position, orientation, and scale) between virtual and real objects to maximize the user’s immersion. In this paper, we compare and explore the effect of passive haptic parameters on the user’s perception by using different transformation conditions in immersive virtual environments. Our experimental study shows that the participants felt the same within a certain range, which seems to support the “minimum cue” theory in giving sufficient sensory stimulation. Thus, considering the benefits of the model using our approach, haptic interaction in VR content can be developed in a more economical way.
Virtual characters are now widely used in games, computer-generated (CG) movies, virtual reality (VR), and communication media. The continued technological innovations in motion capture mean that a more natural representation of a three-dimensional character’s motion should be achievable. Many researchers have investigated how virtual characters interact with their surrounding environment through spatial relationships, which were introduced for adapting and preserving character motion. However, technical problems should be resolved to enable the control of characters in augmented reality (AR) environments that combine with the real world, and this can be achieved by adapting motion to environmental differences using original motion datasets. In this paper, we investigate a novel method for preserving automatic motion adaptation for a virtual character in AR environments. We used specific object (e.g., puddle) recognition and the spatial properties of the user’s surrounding space, e.g., object types and positions, and ran validation experiments to provide accurate motion to improve the AR experience. Our experimental study showed positive results in terms of smooth motion in AR configurations. We also found that the participants using AR felt a greater sense of co-presence with the character through adapted motion.