I need some advice from people experienced with streaming video.
I have a task to put together a system that allows video coming from RS-170 (composite) video cameras and have them displayed on an iPad. The catch is that no wireless (no Wi-Fi, no bluetooth) is allowed. Only a wired interface.
The physical I/O options on an iPad are apparently extremely limited, but I did manage to come across a company named Redpark that makes an RS232-to-Lightning cable. So my proposed solution is to have the video feeds go into a box with software that digitizes and encodes the video, and then sends it over RS232 to the iPad using that cable. The catch here is that the maximum bandwidth on that cable is 115kbps.
My preliminary testing of this setup on a prototype system have been less than stellar so far. I set up two PCs, each with serial ports, and hooked them together with a null modem. I then set the baud rates of the ports to 115kpbs and then attempted to stream a web cam video feed over the serial connection in real-time using ffmpeg. The results weren't very encouraging, but I at least did manage to get some sort of image to show up.
I guess I need to play around with the ffmpeg encoding options some more. But I need to ask: am I wasting my time with this idea, or should what I am asking here be possible?
For SDA LQ standard ("low quality") we encode H.264 mp4 (using x264) with a 128 kbps video track. The hardware decoding on the iPad can play it. It is maximum 320x240 30 fps video. The quality depends heavily on the material. For mostly nonmoving material, it is watchable. If there is a lot of movement or lighting changes, you may not be able to make out much. You can check out some examples at the link. Video game video, but some may be comparable to your application.
Without knowing more about your requirements (resolution, framerate, type of material), it is difficult to say more. However, given the right material, it is definitely possible to do it and have it be watchable (for some definitions of watchable).
Related
I'm looking for a way to reduce a java based media player network bandwidth usage. During my research I found out that quality can be traded for lower datarates on streams with the transcode options. In my case the audio source is in a samba network share (file based - only wav type), and I'm not sure if the transcode setting apply for it.
The source of my problem is that our customer's work site has only a 50Mbit connection to their datacenter, and many clients (~10) has to be able to play back these audio files simultaneously. There is no QoS i guess, and the network is used for other purposes too. Caching is not an option (it's a long story, that i can't tell).
I would be really grateful if someone can clarify it for me. Can I lower the bandwidth requirements in this scenario by lowering the quality with transcode?
I'm open for other suggestions too, if you have an idea.
I'm using a Raspberry Pi 2 to route wifi-eth connections. So from the eth side I have a computer that will connect to internet using the Pi wifi connection. On the Raspberry I started htop to monitor the CPUs load, then on the computer I started chrome and played a 20-minute 1080 video. The load on the CPU didn't seem to go beyond 5% anyhow. After that I closed youtube tab and started a download of a binary file of 5GB from the first row here (https://testdebit.info/). Well, I noticed that CPU load was much more higher, around 10%!
Any explanation of such a difference?
It has to do with compression and how video is encoded. A normal file can be compressed, but nothing like that of a video stream.
A video stream can achieve very high compressions due to the predictable characteristics of video, e.g. video from one frame to another doesn't change much. As such, video will send a whole frame (I-frame) and then update it with just the changes (P-frame). It's even possible to do backward prediction (B-frame). Here's a wikipedia reference.
Yes, I hear your next unspoken question: Doesn't more compression mean more CPU time to uncompress? That's true for a lot of types of compression, such as that used by zip files. But since raw video is not very information dense over time, you have compression techniques that in essence reduce the amount of data you send with very little CPU usage.
I hope this helps.
We are going to develop a Project on Sound Source Localization using Labview. Still We are on intial stage and going to perform all task on Software base with four mic connected with PC (For initial stage, later on going to develop using NI hardware if possible).
Initially we acquireing sound from 4 Different Microphones connected with computer through USB. Here all microhpones acquiring sound from single sound source with some delay(mili seconds) beacuse of their different position. But this Sound data acquired by USB are not able to write to sound card simulteneously. This data of sound acquire some hold time while writing to the sound card and we are getting some delay samples while synchronizaing these all sounds. Is there any idea to reduce this hold time of sounds that writes the data to the sound card?
Suppose hold time 10ms, want to reduce this to the micro seconds of nano seconds.
Reducing of the hold time as well as precise inter-channel synchronisation are not possible with LabVIEW running under Windows, and regular sound acquisition hardware. Internal software delays comparable with the time slice are to be expected (~10ms).
You need at least dedicated acquisition hardware (not a number of USB sound cards), and, if you would like to have precise synchronisation of your output with the input with minimum jitter, you need NI-FPGA. Giving these requirements, I would look at the R-series
I am using OpenCV to capture video streams from two USB webcams (Microsoft LifeCam Studio) in Ubuntu 14.04. I am using very simple VideoCapture code (source here) and am trying to at least view two videos that are synchronized against each other.
I used Android stopwatch apps (UltraChron Stopwatch Lite and Stopwatch Timer) on my Samsung Galaxy S3 mini to realize that my viewed images are out of sync (show different time on stopwatch).
The frames are synced maybe in 50% of the time. The frame time differences I get are from 0 to about 300ms with an average about 120ms. It seems that the amount of timeout used has very little effect on sync (same for 1000ms or 2000ms). I tried to minimize the timeout (waitKey(1) for the OpenCV loop to work at all) and read every Xth iteration of the loop - this gave worse results that waitKey(1000). I run in FullHD but lowering resolution to 640x480 had no effect.
An ideal result would be a 100% synchronized stereo video stream that has X FPS. As I said I so far use OpenCV to view video still images, but I do not mind using anything else to get the desired result (can be on Windows too).
Thanks for help in advance!
EDIT: In my search for low-cost hardware I fount that it is probably possible to do some commodity hardware hacking (link here) and inject a single clock signal into multiple camera modules simultaneously to get the desired sync. The guy who did that seems to have developed his GENLOCKed camera board (called NerdCam1) and even a synced stereo camera board that he now sells for about €200.
However, I have almost zero ability of hardware hacking. Also I am not sure if such clock injection is possible for resolutions above NTSC/PAL standard (as it seems to be an "analog" solution?). Also, I would prefer a variable baseline option where both cameras would not be soldered on a single board.
It is not possible to stereo sync two common webcams because webcams lack external trigger feature that lets one precisely sync multiple cams using a common trigger signal. Such trigger may be done both in SW or HW but the latter will give better precision. Webcams only support "free-running" mode and let you stream whatever FPS they support but you can not influence when exactly the frame integration/exposure is done.
There are USB cameras with a dedicated external trigger feature (usually scientific cameras like Point Grey) - they are more expensive (starting at about $300/piece) than webcams but can be synced. If you really are on low budget you can try to hack the PS3 Eye camera to get the ext. trigger feature.
I have a little wee of a problem developing one of my programs in C++ (Visual studio) - Right now im struggling with connection of multiple webcams (connected via usb cables), creating for each of them separate thread to capture frames, and separate frame for processing image.
I use OpenCV to process frames, but the problem is that i dont get a peak of webcam possibilities (it supports 25 fps, i get only 18) is there some library that i could use to get frames, than process them with OpenCV that would made frames be captured faster?
I was researching a bit and the most popular way is to use directshow to get frames and OpenCV to process them.
Do You agree? Or do You have another solution?
I wouldn't be offended by some links :)
DirectShow is only used, if you open your capture using the
CV_CAP_DSHOW flag, like:
VideoCapture capture( CV_CAP_DSHOW + 0 ); // 0,1,2, your cam id there
(without it, it defaults to vfw )
the capture already runs in a separate thread, so wrapping it with more threads won't give you any gain.
another obstacle with multiple cams is the usb bandwidth, so if you got ports on the back & the front of your machine, dont plug all your cams into the same port/controller else you just saturate it
OpenCV uses DirectShow. Using DirectShow (primary video capture API in Windows) directly will obviously get you par or better performance (and even more likely so if OpenCV is set to use Video for Windows). USB cams typically hit USB bandwidth and hence frame rate limit, using DirectShow to capture in compressed formats or in formats with less bits/pixel is the way to reach higher frame rates within the same USB bandwidth limit.
Another typical problem causing low frame rates is slow synchronous processing delaying the capture. You typically identify this by putting trivial processing into the same capture loop and seeing higher FPS compared to processing-enabled operation.