Proceedings Article | 29 January 2007
Proc. SPIE. 6504, Multimedia Computing and Networking 2007
KEYWORDS: Semantic video, Detection and tracking algorithms, Visualization, Video, Distortion, Computer programming, Video compression, Quantization, Video coding, Scalable video coding
The MPEG-4 Fine Grained Scalability (FGS) profile aims at scalable layered video encoding, in order to ensure efficient
video streaming in networks with fluctuating bandwidths. In this paper, we propose a novel technique, termed as FMOEMR,
which delivers significantly improved rate distortion performance compared to existing MPEG-4 Base Layer
encoding techniques. The video frames are re-encoded at high resolution at semantically and visually important regions
of the video (termed as Features, Motion and Objects) that are defined using a mask (FMO-Mask) and at low resolution
in the remaining regions. The multiple-resolution re-rendering step is implemented such that further MPEG-4
compression leads to low bit rate Base Layer video encoding. The Features, Motion and Objects Encoded-Multi-
Resolution (FMOE-MR) scheme is an integrated approach that requires only encoder-side modifications, and is
transparent to the decoder. Further, since the FMOE-MR scheme incorporates "smart" video preprocessing, it requires
no change in existing MPEG-4 codecs. As a result, it is straightforward to use the proposed FMOE-MR scheme with any
existing MPEG codec, thus allowing great flexibility in implementation. In this paper, we have described, and
implemented, unsupervised and semi-supervised algorithms to create the FMO-Mask from a given video sequence, using
state-of-the-art computer vision algorithms.
