MobiFuse: A High-Precision On-Device Depth Perception System With Multi-Data Fusion

作者：Jinrui Zhang, Deyu Zhang, Tingting Long, Wenxin Chen, Ju Ren, Yunxin Liu, Yudong Zhao, Yaoxue Zhang, Youngki Lee · 发表于：IEEE Transactions on Mobile Computing · 年份：2025 · DOI：10.1109/tmc.2025.3601357 · 被引用次数：3 · 研究领域：Industrial Vision Systems and Defect Detection、Image and Object Detection Techniques、Image Processing Techniques and Applications

We present MobiFuse, a high-precision depth perception system on mobile devices that combines dual RGB and Time-of-Flight (ToF) cameras. To achieve this, we leverage physical principles from various environmental factors to propose the Depth Error Indication (DEI) modality, characterizing the depth error of ToF and stereo-matching. Furthermore, we employ a progressive fusion strategy, merging geometric features from ToF and stereo depth maps with depth error features from the DEI modality to create precise depth maps. Additionally, we create a new ToF-Stereo depth dataset,RealToF, to train and validate our model. Our experiments demonstrate that MobiFuse excels over baselines by significantly reducing depth measurement errors by up to 77.7%. It also showcases strong generalization across diverse datasets and proves effectiveness in two downstream tasks: 3D reconstruction and 3D segmentation. The demo video of MobiFuse in real-life scenarios is available at the de-identified YouTube link.