Human Action Recognition from Video Bitstreams
12/2014 - 05/2015
Project:
Directly using the Motion Vectors (MV) from the compressed MPEG-4 video bitstreams to achieve fast Human Action Recognition, bypassing video decoding process and avoiding pixel-domain analysis.
- Extract MV-based Spatial-temporal Interest Points from video bitstream instead of from the decoded video
- Leverage MV motion features for classification–using traditional BoW and Fisher Vector followed by SVM as the framework.
Related Skills:
- C++
- OpenCV
- FFMPEG
- Linux