Tag Archive for 'video'
http://createdigitalmotion.com
The video for C-Mon & Kypski’s “More is Less” is currently being created from the tastiest of building blocks. The piece is crowdsourced, designed in a way which is eminently viral, gets fans involved, and yet doesn’t really cost the filmmakers much, beyond the back-end programming required to make it all happen.
Of course, the back-end requirements for the piece are not insubstantial, but the execution is flawless: A flash application chooses a frame for you, and cross-fades it with your webcam input so you can get your pose matched up correctly. The capture has a countdown, and allows you to re-shoot your frame if you didn’t get it right the first time.
When you’re done, the system allows you to link to your frame (post yours in comments, here’s mine), so the sharing is more personal.
Continue reading ‘Using crowd–driving recognize mechanics for an stop-motion music video synthesis’
В ряде проектов, в которых я принимал участие – ставилась задача, автоматизировать процесс получения видео файла из произвольного пользовательского контента: изображение + видео файлы + звук.
Данный пост посвящён двум мощнейшим консольным кроссплатформенным инструментам ffmpeg и avisynth.
Continue reading ‘СБОРКА ВИДЕО НА СТОРОНЕ СЕРВЕРА С ПОМОЩЬЮ FFMPEG & AVISYNTH’
1. Install proper ffmpeg:
port install ffmpeg +gpl +lame +x264 +xvid +faac +faad
2. Create an convert.sh file:
#!/bin/sh
mkdir mp4
for file in *.avi; do
/opt/local/bin/ffmpeg -i "$file" -acodec libfaac -ab 128k -ar 48000 \
-s 368x208 -r 29.97 -vcodec libx264 -b 500kb \
-flags +loop -cmp +chroma \
-partitions +parti4x4+partp8x8+partb8x8 \
-me_method umh -subq 6 -trellis 1 \
-refs 2 -bf 1 -coder 1 -me_range 16 -g 300 -keyint_min 25 \
-sc_threshold 40 -i_qfactor 0.71 -maxrate 4M \
-bufsize 4M -qcomp 0.6 -qmin 10 -qmax 51 -qdiff 4 -level 21 \
-threads 0 "mp4/${file%%.*}.mp4"
done
3. Chmod it:
chmod 777 convert.sh
4. launch it:
./convert.sh
P.S. If you want launch conversion in foreground, just do next steps:
- Open terminal and launch virtual console :
screen - launch convertion
./convert.sh - exit virtual console
ctrl+a, d - close terminal window
if you want to sneek, what happens at your virtual console open it with next command:
screen -r
About Xvfb
Xvfb is an X server that can run on machines with no display hardware and no physical input devices. It emulates a dumb framebuffer using virtual memory.
The primary use of this server was intended to be server testing. The mfb or cfb code for any depth can be exercised with this server without the need for real hardware that supports the desired depths. The X community has found many other novel uses for Xvfb, including testing clients against unusual depths and screen configurations, doing batch processing with Xvfb as a background rendering engine, load testing, as an aid to porting the X server to a new platform, and providing an unobtrusive way to run applications that don’t really need an X server but insist on having one anyway.
Compile ffmpeg with x11grab
./configure –enable-gpl –enable-x11grab -extra-ldflags=-L/usr/lib
make
sudo make install
Launch virtual frame buffer and grab video from it
XAUTHORITY=
Xvfb :2 -screen 0 800x600x24 -fbdir &
DISPLAY=:2.0 flashplayer /path/to/your/file.swf &
ffmpeg -f x11grab -vc x264 -s vga -r 30 -b 2000k -g 300 -i :2.0 /path/to/your/file.avi
Tools:
http://valexvir.narod.ru/
http://forum.ixbt.com/topic.cgi?id=20:26019
OpenCV [OpenCV] is an open source (see http://opensource.org) computer vision library available from http://SourceForge.net/projects/opencvlibrary. Th e library is written in C and C++ and runs under Linux, Windows and Mac OS X. Th ere is active development on interfaces for Python, Ruby, Matlab, and other languages.
OpenCV was designed for computational effi ciency and with a strong focus on real-
time applications. OpenCV is written in optimized C and can take advantage of mul-
ticore processors. If you desire further automatic optimization on Intel architectures
[Intel], you can buy Intel’s Integrated Performance Primitives (IPP) libraries [IPP], which consist of low-level optimized routines in many diff erent algorithmic areas. OpenCV automatically uses the appropriate IPP library at runtime if that library is installed.
One of OpenCV’s goals is to provide a simple-to-use computer vision infrastructure
that helps people build fairly sophisticated vision applications quickly. Th e OpenCV
library contains over 500 functions that span many areas in vision, including factory
product inspection, medical imaging, security, user interface, camera calibration, stereo vision, and robotics. Because computer vision and machine learning oft en go hand-in- hand, OpenCV also contains a full, general-purpose Machine Learning Library (MLL). Th is sublibrary is focused on statistical pattern recognition and clustering. Th e MLL is highly useful for the vision tasks that are at the core of OpenCV’s mission, but it is general enough to be used for any machine learning problem.
Рекламный ролик с персонажем созданным для WIF-2006, основанный на MOCAP.
Adam comercials from peko on Vimeo.