Virtual Reality (VR) has a great potential to improve skills of Deaf and Hard-of-Hearing (DHH) people. Most VR applications and devices are designed for persons without hearing problems. Therefore, DHH persons have many limitations when using VR. Adding special features in a VR environment, such as subtitles, or haptic devices will help them. Previously, it was necessary to design a special VR environment for DHH persons. We introduce and evaluate a new prototype called "EarVR" that can be mounted on any desktop or mobile VR Head-Mounted Display (HMD). EarVR analyzes 3D sounds in a VR environment and locates the direction of the sound source that is closest to a user. It notifies the user about the sound direction using two vibro-motors placed on the user's ears. EarVR helps DHH persons to complete sound-based VR tasks in any VR application with 3D audio and a mute option for background music. Therefore, DHH persons can use all VR applications with 3D audio, not only those applications designed for them. Our user study shows that DHH participants were able to complete a simple VR task significantly faster with EarVR than without. The completion time of DHH participants was very close to participants without hearing problems. Also, it shows that DHH participants were able to finish a complex VR task with EarVR, while without it, they could not finish the task even once. Finally, our qualitative and quantitative evaluation among DHH participants indicates that they preferred to use EarVR and it encouraged them to use VR technology more.

This paper presents a novel method for illumination estimation from RGB-D images. The main focus of the proposed method is to enhance visual coherence in augmented reality applications by providing accurate and temporally coherent estimates of real illumination. For this purpose, we designed and trained a deep neural network which calculates a dominant light direction from a single RGB-D image. Additionally, we propose a novel method for real-time outlier detection to achieve temporally coherent estimates. Our method for light source estimation in augmented reality was evaluated on the set of real scenes. Our results demonstrate that the neural network can successfully estimate light sources even in scenes which were not seen by the network during training. Moreover, we compared our results with illumination estimates calculated by the state-of-the-art method for illumination estimation. Finally, we demonstrate the applicability of our method on numerous augmented reality scenes.

Augmented reality has a high potential in interior design due to its capability of visualizing numerous prospective designs directly in a target room. In this paper, we present our research on utilization of augmented reality for interactive and personalized furnishing. We propose a new algorithm for automated interior design which generates sensible and personalized furniture configurations. This algorithm is combined with mobile augmented reality system to provide a user with an interactive interior design try-out tool. Personalized design is achieved via a recommender system which uses user preferences and room data as input. We conducted three user studies to explore different aspects of our research. The first study investigated the user preference between augmented reality and on-screen visualization for interactive interior design. In the second user study, we studied the user preference between our algorithm for automated interior design and optimization-based algorithm. Finally, the third study evaluated the probability of sensible design generation by the compared algorithms. The main outcome of our research suggests that augmented reality is viable technology for interactive home furnishing.

Sound source localization is important for spatial awareness and immersive Virtual Reality (VR) experiences. Deaf and Hard-of-Hearing (DHH) persons have limitations in completing sound-related VR tasks efficiently because they perceive audio information differently. This paper presents and evaluates a special haptic VR suit that helps DHH persons efficiently complete sound-related VR tasks. Our proposed VR suit receives sound information from the VR environment wirelessly and indicates the direction of the sound source to the DHH user by using vibrotactile feedback. Our study suggests that using different setups of the VR suit can significantly improve VR task completion times compared to not using a VR suit. Additionally, the results of mounting haptic devices on different positions of users’ bodies indicate that DHH users can complete a VR task significantly faster when two vibro-motors are mounted on their arms and ears compared to their thighs. Our quantitative and qualitative analysis demonstrates that DHH persons prefer using the system without the VR suit and prefer mounting vibro-motors in their ears. In an additional study, we did not find a significant difference in task completion time when using four vibro-motors with the VR suit compared to using only two vibro-motors in users’ ears without the VR suit.