A scalable representation for motion vectors for rate adaptation to network constraints

Ugur Sezer; Seyfullah Halit Oguz

doi:10.1117/12.503312

23 June 2003 A scalable representation for motion vectors for rate adaptation to network constraints

Ugur Sezer, Seyfullah Halit Oguz

Proceedings Volume 5150, Visual Communications and Image Processing 2003; (2003) https://doi.org/10.1117/12.503312
Event: Visual Communications and Image Processing 2003, 2003, Lugano, Switzerland

Abstract

There is a growing need for mechanisms to shape the rate of precompressed video for adaptation to network constraints. The motion vector data component in an encoded bitstream might constitute some considerable portion of P and especially B type pictures, yet no technique currently exists to scale it. Motion vectors of neighboring macroblocks tend to be well-correlated in both horizontal and vertical directions. However, the current standards only exploit the horizontal correlations through predictive coding, introducing dependency and thus resulting in a nonscalable representation. In this paper, we propose a new representation and encoding algorithm for the motion vector information enabling the exploitation of two-dimensional (2-D) correlations, and realizing the signal-to-noise ratio (SNR) scaling of an already encoded video object to an alternate (lower) rate - (higher) distortion level. In the proposed approach, the values of the motion vectors are represented in a binary format. Consequently, the individual bit planes of this representation are coded through a novel 2-D hierarchical bit plane encoding scheme. Scaling, when necessary, is achieved by discarding the least significant bit plane(s). Simulations based on MPEG-2 standard demonstrate that up to 20% scaling is achievable without visually noticeable distortion.

Citation Download Citation

Ugur Sezer and Seyfullah Halit Oguz "A scalable representation for motion vectors for rate adaptation to network constraints", Proc. SPIE 5150, Visual Communications and Image Processing 2003, (23 June 2003); https://doi.org/10.1117/12.503312

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
10 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Computer programming

Binary data

Video

Signal to noise ratio

Distortion

Video coding

Video compression

Show All Keywords

Keywords/Phrases

Search In:

Publication Years