2019年AI和ffmpeg_gstreamer的应用实践.pdf

1、AI和FFmpeg/gstreamerAgenda FFmpeg Gstreamer FeatherNet for face anti-spoofingFFMPEGFFmpeg is the most popular open-source multimedia manipulation tools with a library of plugins that can be applied to various parts of the audio and video processing pipelines and have achieved wide adoption across the

2、 world Video encoding,decoding and transcoding are some of the most popular applications of FFmpeg,and Multiplatform is supported such as Linux/Android/Windows.ffmpeg-qsv and ffmpeg-vaapi are providing HW acceleration for intel platforms.repo link:https:/git.ffmpeg.org/ffmpeg.githttps:/git.libav.org

3、/FFmpegDNN in FFmpegGuo YejunDNN in FFmpegGstreamer结构9FeatherNet for Face Antispoofing10Face Anti-spoofing competitionCVPR2019us11Feather for(Face Anti-spoofing)next level details数据源由Intel realsense采集12Feather:Feathernet,MobileLiteNetA/BOur Model:as lite as FeatherMore preciseBlocks used in FeatherN

4、etsBN ReLU63x3 DWConv1x1 Conv1x1 ConvBN ReLU66 x ccBNOutputInputcAddAddBN ReLU61x1 Conv1x1 ConvBN ReLU6BNOutputInput1x1 Conv6 x c2x2 AVG Pool(stride=2)3x3 DWConv(stride=2)BNBlockB:Down-Sampling BlockBlockA:Inverted Residual BlockccccApproachcBN ReLU61x1 Conv1x1 ConvBN ReLU6BNOutputInput6 x c3x3 DWCo

5、nv(stride=2)cBlockC:Down-Sampling BlockWithout AVGPoolingFeatherNetA-BlockA,BlockCFeatherNetB-BloackA,BlockBNetwork ArchitectureApproachStreaming ModuleThe last blocks output is down-sampledby a depth-wise convolution layer and flattened directly into a feature vector.ApproachStreaming Module Approa

6、chRF of center unitRF of corner unitLast 7x 7 Feature Map(one channel)Input Image Units at different position in feature map correspond different receptive field ExperimentsA Newly Collected Dataset:Multi-Modal Face Dataset(MMFD)Intel RealSense SR300 depth camera is utilized 1500