Perceptual Issues and an Improvement Method for User Perspective Rendering in Augmented Reality
IEEE Access, cilt.14, ss.74660-74672, 2026 (SCI-Expanded, Scopus)
- Yayın Türü: Makale / Tam Makale
- Cilt numarası: 14
- Basım Tarihi: 2026
- Doi Numarası: 10.1109/access.2026.3693313
- Dergi Adı: IEEE Access
- Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Compendex, INSPEC, Directory of Open Access Journals
- Sayfa Sayıları: ss.74660-74672
- Anahtar Kelimeler: Augmented reality, handheld mobile AR, head-coupled rendering, homography, magic lens, perspective mismatch, user perspective rendering
- Ankara Yıldırım Beyazıt Üniversitesi Adresli: Evet
Özet
Augmented Reality (AR) enables real-time interactive experiences by overlaying computer-generated content onto the physical world. In handheld mobile AR, the scene is typically rendered from the rear camera viewpoint rather than the user's actual viewpoint, which introduces a perspective mismatch and reduces visual plausibility. To address this issue without additional hardware, we present a real-time mobile AR approach that estimates the user's viewpoint from front-camera face tracking and reprojects the rear-camera background using a homography-based reprojection matrix. We conducted two controlled user studies to quantitatively evaluate perceptual performance in (i) size estimation and (ii) depth estimation tasks. The results show that the proposed user-perspective reprojection significantly improves size perception and visual alignment compared to conventional device-perspective rendering. However, no consistent improvement is observed in depth perception under the evaluated marker-based setup, highlighting the limitations of planar reprojection when depth cues such as motion parallax are restricted. Overall, the findings demonstrate that head-coupled user-perspective reprojection can improve perceptual consistency in mobile AR, particularly for size-critical tasks. Unlike prior work that primarily focuses on rendering techniques or interaction performance, this study provides a controlled perceptual analysis that isolates viewpoint-induced scale distortions from depth-related cues. In this sense, the contribution of this work is not only algorithmic but also perceptual, offering empirical insight into when and why user perspective rendering improves spatial perception in mobile AR.