Smartphone Augmented Reality Applications for Tourism

Invisible, attentive and adaptive technologies that provide tourists with relevant services and information anytime and anywhere may no longer be a vision from the future. The new display paradigm, stemming from the synergy of new mobile devices, context-awareness and AR, has the potential to enhance tourists’ experiences and make them exceptional. However, effective and usable design is still in its infancy. In this publication we present an overview of current smartphone AR applications outlining tourism-related domain-specific design challenges. This study is part of an ongoing research project aiming at developing a better understanding of the design space for smartphone context-aware AR applications for tourists

Occlusion Handling using Semantic Segmentation and Visibility-Based Rendering for Mixed Reality

Real-time occlusion handling is a major problem in outdoor mixed reality system because it requires great computational cost mainly due to the complexity of the scene. Using only segmentation, it is difficult to accurately render a virtual object occluded by complex objects such as trees, bushes etc. In this paper, we propose a novel occlusion handling method for real-time, outdoor, and omni-directional mixed reality system using only the information from a monocular image sequence. We first present a semantic segmentation scheme for predicting the amount of visibility for different type of objects in the scene. We also simultaneously calculate a foreground probability map using depth estimation derived from optical flow. Finally, we combine the segmentation result and the probability map to render the computer generated object and the real scene using a visibility-based rendering method. Our results show great improvement in handling occlusions compared to existing blending based methods

Reviving the Euston Arch: A Mixed Reality Approach to Cultural Heritage Tours

Augmented Reality (AR) and Virtual Reality (VR) users have distinct capabilities and experiences during Extended Reality (XR) collaborations: while AR users benefit from real-time contextual information due to physical presence, VR users enjoy the flexibility to transition between locations rapidly, unconstrained by physical space.Our research aims to utilize these spatial differences to facilitate engaging, shared XR experiences. Using Google Geospatial Creator, we enable large-scale outdoor authoring and precise localization to create a unified environment. We integrated Ubiq to allow simultaneous voice communication, avatar-based interaction and shared object manipulation across platforms.We apply AR and VR technologies in cultural heritage exploration. We selected the Euston Arch as our case study due to its dramatic architectural transformations over time. We enriched the co-exploration experience by integrating historical photos, a 3D model of the Euston Arch, and immersive audio narratives into the shared AR/VR environment

Evaluation of CNN-based Single-Image Depth Estimation Methods

While an increasing interest in deep models for single-image depth estimation methods can be observed, established schemes for their evaluation are still limited. We propose a set of novel quality criteria, allowing for a more detailed analysis by focusing on specific characteristics of depth maps. In particular, we address the preservation of edges and planar regions, depth consistency, and absolute distance accuracy. In order to employ these metrics to evaluate and compare state-of-the-art single-image depth estimation approaches, we provide a new high-quality RGB-D dataset. We used a DSLR camera together with a laser scanner to acquire high-resolution images and highly accurate depth maps. Experimental results show the validity of our proposed evaluation protocol