在上周关于多台摄像机的英特尔在线研讨会上,RealSense首席技术官表示,随着更多摄像头的增加,将需要更高规格的PC硬件来应对这种压力(例如,配备英特尔i7处理器的机器)。
在同一个研讨会上,他们说他们开发了一种新的'x3'数据压缩算法,可以连接更多的摄像头。
他们没有给出开启时间的日期,但是他们一直在努力从相机中挤出更高的性能。
他们还开发了一种“改进的霍夫曼”算法,可以在多种摄像机配置中提供更多的通道。
下面是相机文件中关于在多达6台摄像机的非同步集线器上使用带宽的图表。
左键单击图像以查看完整尺寸
您也可以使用多台PC,并使用硬件同步电缆将摄像机集中在一起。
这是英特尔在1月的圣丹斯电影节上采用多相机演示的方法。
他们有4台摄像机,每台摄像机连接到i7 PC,并自动将数据传输到第5台PC,将它们全部同步。
该过程在下面的文章中描述,其中他们谈论使用8个或更多相机。
Volumetric Capture @ Sundance使用英特尔实感深度相机
以上来自于谷歌翻译
以下为原文
In an Intel online seminar about multiple cameras last week, the RealSense CTO said that as more cameras are added, a higher spec of PC hardware will be needed to cope with the strain (for example, a machine with an Intel i7 processor). In the same seminar, they said that they have developed a new 'x3' data compression algorithm that will allow more cameras to be attached. They did not give a date for when that will be switched on, but they are continuously working on squeezing greater performance out of the cameras.
They have also developed a 'Modified Huffman' algorithm that will give a greater number of channels in multiple camera configurations.
Below is a chart from the camera paper about bandwidth use on a non-synced hub of up to 6 cameras. Left-click on the image to see it in full size.1
You can alternatively use multiple PCs and collectively join the cameras together using hardware sync cabling. This was the approach Intel took with a multiple-camera demo at the Sundance Festival in January. They had 4 cameras, each one connected to an i7 PC, and transferred the data automatically to a 5th PC to sync it all together. The process is described in the article below, in which they talk about using 8 or more cameras.
Volumetric Capture @ Sundance using Intel RealSense Depth Cameras