FMOE-MR: content-driven multiresolution MPEG-4 fine grained scalable layered video encoding

Abstract

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 FMOE-MR, 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-MultiResolution (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.

Efficient dissemination of personalized video content in resource-constrained environments

“…GDS (Greedy-Dual-Size): The GDSF cache replacement algorithm [13] uses a retention value given by. retention_value = Latency/ Size In addition to removing files with the minimum retention value during a cache replacement, the GDS algorithm also subtracts this minimum retention-value from the retentionvalue for each of the other files in the cache.…”