Markerless Vision‐Based Augmented Reality for Urban Planning

Abstract

Augmented Reality (AR) is a rapidly developing field with numerous potential applications. For example, building developers, public authorities, and other construction industry stakeholders need to visually assess potential new developments with regard to aesthetics, health and safety, and other criteria. Current state‐of‐the‐art visualization technologies are mainly fully virtual, while AR has the potential to enhance those visualizations by observing proposed designs directly within the real environment. A novel AR system is presented, that is most appropriate for urban applications. It is based on monocular vision, is markerless, and does not rely on beacon‐based localization technologies (like GPS) or inertial sensors. Additionally, the system automatically calculates occlusions of the built environment on the augmenting virtual objects. Three datasets from real environments presenting different levels of complexity (geometrical complexity, textures, occlusions) are used to demonstrate the performance of the proposed system. Videos augmented with our system are shown to provide realistic and valuable visualizations of proposed changes of the urban environment. Limitations are also discussed with suggestions for future work.

The educational possibilities of Augmented Reality

“…According to various authors (Fundación Telefónica, 2011;Kipper & Rampolla, 2012), it is possible to use AR in a wide variety of fields: advertising, navigation and city guides, industry, art, language learning, travel and tourist guides, medicine, marketing and sales, entertainment and games, social networks, education, and translation. As far as education is concerned, the first thing which needs to be highlighted is that different experiences and research initiatives related to AR utilization have recently been undertaken at various educational levels: primary education (Bongiovani, 2013); lower and upper secondary education/vocational training (Avendaño, Chao, & Mercado, 2012;Bressler & Bodzin, 2013 (Carozza et al, 2012;De la Torre et al, 2013;Redondo et al, 2012); town-planning (Carozza, Tingdahl, & Gool, 2014), mathematics-geometry (Avendaño et al, 2012;Bujak, Radu, Catrambone, MacIntyre, Zheng, & Golubski, 2013;De Pedro Carracedo & Méndez, 2012); art and history (Ruiz, 2011); language learning (Emma, Liu, Tsai, PeiHsun, & Ming-Kuan Tsai, 2013;Liu, 2009); technology (Rodríguez, 2013); design (Ko, Chang, Chen, & Hua, 2011); chemistry (Núñez et al, 2008;Pasaréti et al, 2011); física (LinT et al, 2013); or geography (Klopfer & Squire, 2008;Tsai, Liu, & Yau, 2013).…”

High-precision vision-based mobile augmented reality system for context-aware architectural, engineering, construction and facility management (AEC/FM) applications

“…Despite the fact that these systems rely on tracking the camera position and orientation, and does not require additional infrastructure, such systems still require a large amount of matching to be conducted at each step. As reported by Carozza et al (2012), the overall tracking is likely not as efficient as tracking image features.…”

“…Some researchers have proved that the fused (aligned) cyber-physical model is accurate to within millimeters (Golparvar-Fard et al 2011) and can be used to predict the actual construction progress versus the planned cyber model with high accuracy, even when visual obstructions are present (2010). Recent works such as Carozza et al (2012) extend marker-less augmented reality systems for urban planning purposes. Despite the fact that these systems rely on tracking the camera position and orientation, and does not require additional infrastructure, such systems still require a large amount of matching to be conducted at each step.…”

“…Recent advances in image processing and computer vision have led to new research on the application of image-based reasoning for various construction management tasks and techniques that can manually, semiautomatically, and automatically interpret them (Cheng and Chen 2002;Carozza et al 2012;Golparvar-Fard et al 2010Kiziltas et al 2008). These researches have shown that a set of overlapping images can be used to extract accurate 3D geometry of stationary objects such as buildings under construction.…”

Towards Gesture-Based Multi-User Interactions In Collaborative Virtual Environments

“…The design and development of computer games, arts, fashion, digital storytelling and advertising are just a few of the application domains where immersive VR is already exploited. Thanks to improved rendering techniques, more accurate inertial sensors and natural interactive tools, VR has also begun to be employed in therapy clinics (Spicer et al, 2017), architecture (Vorlander et al, 2015), urban planning (Carrozza et al, 2014), museum tours (Carrozzino and Bergamasco, 2010), education (Greenwald et al, 2017a) and forensic investigations (Ebert et al, 2014). In forensics for example, crime scenes are nowadays routinely replicated in 3D, and VR can be a cost-effective solution to observe a scene from various viewpoints, such as a victim's view and a witness' view (Burton et al, 2005).…”