ﻻ يوجد ملخص باللغة العربية
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 devices 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.
We propose DeepMultiCap, a novel method for multi-person performance capture using sparse multi-view cameras. Our method can capture time varying surface details without the need of using pre-scanned template models. To tackle with the serious occlus
Aiming at automatic, convenient and non-instrusive motion capture, this paper presents a new generation markerless motion capture technique, the FlyCap system, to capture surface motions of moving characters using multiple autonomous flying cameras (
Coordinating the operations of separate wireless systems at the wavelength level can lead to significant improvements in wireless capabilities. We address a fundamental challenge in distributed radio frequency system cooperation - inter-node phase al
Electric Vehicles are increasingly common, with inductive chargepads being considered a convenient and efficient means of charging electric vehicles. However, drivers are typically poor at aligning the vehicle to the necessary accuracy for efficient
In 2015/16, the photomultiplier cameras of the H.E.S.S. Cherenkov telescopes CT1-4 have undergone a major upgrade. The entire electronics has been replaced, using NECTAr chips for the front-end readout. A new ventilation system has been installed and