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  • 1.
    Kasperi, Johan
    et al.
    KTH, School of Computer Science and Communication (CSC).
    Picha Edwardsson, Malin
    KTH, School of Computer Science and Communication (CSC), Media Technology and Interaction Design, MID.
    Romero, Mario
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Occlusion in outdoor Augmented Reality using geospatial building data2017In: VRST '17 Proceedings of the 23rd ACM Symposium on Virtual Reality Software and Technology, Association for Computing Machinery (ACM), 2017, Vol. Part F131944, article id a30Conference paper (Refereed)
    Abstract [en]

    Aligning virtual and real objects in Augmented Reality (AR) is essential for the user experience. Without alignment, the user loses suspension of disbelief and the sense of depth, distance, and size. Occlusion is a key feature to be aligned. Virtual content should be partially or fully occluded if real world objects are in its line-of-sight. The challenge for simulating occlusion is to construct the geometric model of the environment. Earlier studies have aimed to create realistic occlusions, yet most have either required depth-sensing hardware or a static predened environment. is paper proposes and evaluates an alternative model-based method for dynamic outdoor AR of virtual buildings rendered on non depth-sensing smartphones. It uses geospatial data to construct the geometric model of real buildings surrounding the virtual building. The method removes the target regions from the virtual building using masks constructed from real buildings. While the method is not pixel-perfect, meaning that the simulated occlusion is not fully realistic, results from the user study indicate that it fullled its goal. A majority of the participants expressed that their experience and depth perception improved with the method activated. The result from this study has applications to mobile AR since the majority of smartphones are not equipped with depth sensors. Using geospatial data for simulating occlusions is a suciently eective solution until depth-sensing AR devices are more widely available.

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