We present a method for precisely time-synchronizing the capture of image sequences from a collection of smartphone cameras connected over WiFi. Our method is entirely software-based, has only modest hardware requirements, and achieves an accuracy of less than 250 microseconds on unmodified commodity hardware. It does not use image content and synchronizes cameras prior to capture. The algorithm operates in two stages. In the first stage, we designate one device as the leader and synchronize each client device's clock to it by estimating network delay. Once clocks are synchronized, the second stage initiates continuous image streaming, estimates the relative phase of image timestamps between each client and the leader, and shifts the streams into alignment. We quantitatively validate our results on a multi-camera rig imaging a high-precision LED array and qualitatively demonstrate significant improvements to multi-view stereo depth estimation and stitching of dynamic scenes. We release as open source 'libsoftwaresync', an Android implementation of our system, to inspire new types of collective capture applications.
Investigation of Color Constancy for Ubiquitous Wireless LAN/Camera Positioning: An Initial Outcome
Faculty of Computer Science & Information Systems, Universiti Teknologi Malaysia（马来西亚理工大学计算机科学与信息系统学院）；Centre of Real Estate Studies, Universiti Teknologi Malaysia（马来西亚理工大学房地产研究中心）
Tensor-Based Synchronization and the Low-Rankness of the Block Trifocal Tensor
School of Mathematics, University of Minnesota（明尼苏达大学数学学院）；Oden Institute for Computational Engineering and Sciences, University of Texas at Austin（德克萨斯大学奥斯汀分校奥登计算工程与科学学院）
QuadSync: Quadrifocal Tensor Synchronization via Tucker Decomposition
School of Mathematics, University of Minnesota（明尼苏达大学数学系）；Department of Mathematics and Oden Institute for Computational Engineering and Sciences, University of Texas at Austin（德克萨斯大学奥斯汀分校数学系和计算工程与科学学院）
